This repo is a collection of AWESOME things about domain adaptation, including papers, code, etc. Feel free to star and fork.
Contents
- awesome-domain-adaptation
- Contents
- Papers
- Survey
- Theory
- Explainable
- Unsupervised DA
- Semi-supervised DA
- Weakly-Supervised DA
- Zero-shot DA
- One-shot DA
- Few-shot UDA
- Few-shot DA
- Partial DA
- Open Set DA
- Universal DA
- Open Compound DA
- Multi Source DA
- Multi Target DA
- Incremental DA
- Multi Step DA
- Heterogeneous DA
- Target-agnostic DA
- Federated DA
- Continuously Indexed DA
- Source Free DA
- Model Selection
- Other Transfer Learning Paradigms
- Applications
- Related Topics
- Benchmarks
- Library
- Lectures and Tutorials
- Other Resources
Papers
Survey
Arxiv
- A Survey on Deep Domain Adaptation for LiDAR Perception [7 Jun 2021]
- A Comprehensive Survey on Transfer Learning [7 Nov 2019]
- Transfer Adaptation Learning: A Decade Survey [12 Mar 2019]
- A review of single-source unsupervised domain adaptation [16 Jan 2019]
- An introduction to domain adaptation and transfer learning [31 Dec 2018]
- A Survey of Unsupervised Deep Domain Adaptation [6 Dec 2018]
- Transfer Learning for Cross-Dataset Recognition: A Survey [2017]
- Domain Adaptation for Visual Applications: A Comprehensive Survey [2017]
Journal
- A Review of Single-Source Deep Unsupervised Visual Domain Adaptation [TNNLS 2020]
- Deep Visual Domain Adaptation: A Survey [Neurocomputing 2018]
- A Survey on Deep Transfer Learning [ICANN2018]
- Visual domain adaptation: A survey of recent advances [2015]
Theory
Arxiv
- A Theory of Label Propagation for Subpopulation Shift [22 Feb 2021]
- A General Upper Bound for Unsupervised Domain Adaptation [3 Oct 2019]
- On Deep Domain Adaptation: Some Theoretical Understandings [arXiv 15 Nov 2018]
Conference
- Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift [NeurIPS 2020]
- Bridging Theory and Algorithm for Domain Adaptation [ICML2019] [Pytorch]
- On Learning Invariant Representation for Domain Adaptation [ICML2019] [code]
- Unsupervised Domain Adaptation Based on Source-guided Discrepancy [AAAI2019]
- Learning Bounds for Domain Adaptation [NIPS2007]
- Analysis of Representations for Domain Adaptation [NIPS2006]
Journal
- On a Regularization of Unsupervised Domain Adaptation in RKHS [ACHA2021]
- Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]
- On generalization in moment-based domain adaptation [AMAI2020]
- A theory of learning from different domains [ML2010]
Explainable
Conference
- Visualizing Adapted Knowledge in Domain Transfer [CVPR2021] [Pytorch]
Unsupervised DA
Adversarial Methods
Conference
- ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptation [NeurIPS2021] [Pytorch]
- MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation [CVPR2021] [Pytorch]
- Self-adaptive Re-weighted Adversarial Domain Adaptation [IJCAI2020]
- DIRL: Domain-Invariant Reperesentation Learning Approach for Sim-to-Real Transfer [CoRL2020] [Project]
- Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation [ECCV2020] [PyTorch]
- Gradually Vanishing Bridge for Adversarial Domain Adaptation [CVPR2020] [Pytorch]
- Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation [ICML2020] [Pytorch]
- Adversarial-Learned Loss for Domain Adaptation [AAAI2020]
- Structure-Aware Feature Fusion for Unsupervised Domain Adaptation [AAAI2020]
- Adversarial Domain Adaptation with Domain Mixup [AAAI2020] [Pytorch]
- Discriminative Adversarial Domain Adaptation [AAAI2020] [Pytorch]
- Bi-Directional Generation for Unsupervised Domain Adaptation [AAAI2020]
- Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning [ICASSP 2020]
- Curriculum based Dropout Discriminator for Domain Adaptation [BMVC2019] [Project]
- Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition [IJCNN2019] [Matlab]
- Transfer Learning with Dynamic Adversarial Adaptation Network [ICDM2019]
- Joint Adversarial Domain Adaptation [ACM MM2019]
- Cycle-consistent Conditional Adversarial Transfer Networks [ACM MM2019] [Pytorch]
- Learning Disentangled Semantic Representation for Domain Adaptation [IJCAI2019] [Tensorflow]
- Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation [ICML2019] [Pytorch]
- Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers [ICML2019] [Pytorch]
- Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation [ICCV2019] [PyTorch]
- Cluster Alignment with a Teacher for Unsupervised Domain Adaptation [ICCV2019] [Tensorflow]
- Unsupervised Domain Adaptation via Regularized Conditional Alignment [ICCV2019]
- Attending to Discriminative Certainty for Domain Adaptation [CVPR2019] [Project]
- GCAN: Graph Convolutional Adversarial Network for Unsupervised Domain Adaptation [CVPR2019]
- Domain-Symmetric Networks for Adversarial Domain Adaptation [CVPR2019] [Pytorch]
- DLOW: Domain Flow for Adaptation and Generalization [CVPR2019 Oral]
- Progressive Feature Alignment for Unsupervised Domain Adaptation [CVPR2019] [Tensorflow]
- Gotta Adapt ’Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild [CVPR2019]
- Looking back at Labels: A Class based Domain Adaptation Technique [IJCNN2019] [Project]
- Consensus Adversarial Domain Adaptation [AAAI2019]
- Transferable Attention for Domain Adaptation [AAAI2019]
- Exploiting Local Feature Patterns for Unsupervised Domain Adaptation [AAAI2019]
- Augmented Cyclic Adversarial Learning for Low Resource Domain Adaptation [ICLR2019]
- Conditional Adversarial Domain Adaptation [NIPS2018] [Pytorch(official)] [Pytorch(third party)]
- Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model [ECCV2018]
- Deep Adversarial Attention Alignment for Unsupervised Domain Adaptation: the Benefit of Target Expectation Maximization [ECCV2018]
- Learning Semantic Representations for Unsupervised Domain Adaptation [ICML2018] [TensorFlow(Official)]
- CyCADA: Cycle-Consistent Adversarial Domain Adaptation [ICML2018] [Pytorch(official)]
- From source to target and back: Symmetric Bi-Directional Adaptive GAN [CVPR2018] [Keras(Official)] [Pytorch]
- Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation [CVPR2018] [Tensorflow]
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation [CVPR2018] [Pytorch(Official)]
- Adversarial Feature Augmentation for Unsupervised Domain Adaptation [CVPR2018] [TensorFlow(Official)]
- Duplex Generative Adversarial Network for Unsupervised Domain Adaptation [CVPR2018] [Pytorch(Official)]
- Generate To Adapt: Aligning Domains using Generative Adversarial Networks [CVPR2018] [Pytorch(Official)]
- Image to Image Translation for Domain Adaptation [CVPR2018]
- Unsupervised Domain Adaptation with Similarity Learning [CVPR2018]
- Conditional Generative Adversarial Network for Structured Domain Adaptation [CVPR2018]
- Collaborative and Adversarial Network for Unsupervised Domain Adaptation [CVPR2018] [Pytorch]
- Re-Weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation [CVPR2018]
- Multi-Adversarial Domain Adaptation [AAAI2018] [Caffe(Official)]
- Wasserstein Distance Guided Representation Learning for Domain Adaptation [AAAI2018] [TensorFlow(official)] [Pytorch]
- Incremental Adversarial Domain Adaptation for Continually Changing Environments [ICRA2018]
- Adversarial Dropout Regularization [ICLR2018]
- A DIRT-T Approach to Unsupervised Domain Adaptation [ICLR2018 Poster] [Tensorflow(Official)]
- Label Efficient Learning of Transferable Representations acrosss Domains and Tasks [NIPS2017] [Project]
- Adversarial Discriminative Domain Adaptation [CVPR2017] [Tensorflow(Official)] [Pytorch]
- Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks [CVPR2017] [Tensorflow(Official)] [Pytorch]
- Domain Separation Networks [NIPS2016]
- Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation [ECCV2016]
- Domain-Adversarial Training of Neural Networks [JMLR2016]
- Unsupervised Domain Adaptation by Backpropagation [ICML2015] [Caffe(Official)] [Tensorflow] [Pytorch]
Journal
- Incremental Unsupervised Domain-Adversarial Training of Neural Networks [TNNLS 2020]
- Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]
- Adversarial Learning and Interpolation Consistency for Unsupervised Domain Adaptation [IEEE ACCESS]
- TarGAN: Generating target data with class labels for unsupervised domain adaptation [Knowledge-Based Systems]
Arxiv
- Bi-Directional Generation for Unsupervised Domain Adaptation [12 Feb 2020]
- Enlarging Discriminative Power by Adding an Extra Class in Unsupervised Domain Adaptation [19 Feb 2020] [Tensorflow]
- Learning Domain Adaptive Features with Unlabeled Domain Bridges [10 Dec 2019]
- Reducing Domain Gap via Style-Agnostic Networks [25 Oct 2019]
- Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment [23 Oct 2019]
- Adversarial Variational Domain Adaptation [25 Sep 2019]
- Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation [arXiv 13 Sep 2019]
- SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation [arXiv 11 Jun 2019]
- Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation [arXiv 10 Jun 2019]
- Adversarial Domain Adaptation Being Aware of Class Relationships [arXiv 28 May 2019]
- Domain-Invariant Adversarial Learning for Unsupervised Domain Adaption [arXiv 30 Nov 2018]
- Unsupervised Domain Adaptation using Deep Networks with Cross-Grafted Stacks [arXiv 17 Feb 2019]
- DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification [arXiv 30 Dec 2018]
- Unsupervised Domain Adaptation using Generative Models and Self-ensembling [arXiv 2 Dec 2018]
- Domain Confusion with Self Ensembling for Unsupervised Adaptation [arXiv 10 Oct 2018]
- Improving Adversarial Discriminative Domain Adaptation [arXiv 10 Sep 2018]
- M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning [arXiv 6 Jul 2018] [Pytorch(official)]
- Factorized Adversarial Networks for Unsupervised Domain Adaptation [arXiv 4 Jun 2018]
- DiDA: Disentangled Synthesis for Domain Adaptation [arXiv 21 May 2018]
- Unsupervised Domain Adaptation with Adversarial Residual Transform Networks [arXiv 25 Apr 2018]
- Causal Generative Domain Adaptation Networks [arXiv 28 Jun 2018]
Distance-based Methods
Journal
- Transferable Representation Learning with Deep Adaptation Networks [TPAMI]
- Robust unsupervised domain adaptation for neural networks via moment alignment [InfSc2019]
Conference
- Domain Conditioned Adaptation Network [AAAI2020] [Pytorch]
- HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation [AAAI2020] [Tensorflow]
- Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation [ICCV2019]
- Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation [AAAI2019]
- Residual Parameter Transfer for Deep Domain Adaptation [CVPR2018]
- Deep Asymmetric Transfer Network for Unbalanced Domain Adaptation [AAAI2018]
- Central Moment Discrepancy for Unsupervised Domain Adaptation [ICLR2017], [InfSc2019], [code]
- Deep CORAL: Correlation Alignment for Deep Domain Adaptation [ECCV2016]
- Learning Transferable Features with Deep Adaptation Networks [ICML2015][code]
- Unsupervised Domain Adaptation with Residual Transfer Networks [NIPS2016] [code]
- Deep Transfer Learning with Joint Adaptation Networks [ICML2017] [code]
Arxiv
- Deep Domain Confusion: Maximizing for Domain Invariance [Arxiv 2014]
Information-based Methods
- Hypothesis Disparity Regularized Mutual Information Maximization [AAAI2021]
Optimal Transport
Conference
- MOST: Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning [UAI2021]
- LAMDA: Label Matching Deep Domain Adaptation [ICML2021]
- TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport [IJCAI2021]
- Unbalanced minibatch Optimal Transport; applications to Domain Adaptation [ICML2021] [Pytorch]
- Graph Optimal Transport for Cross-Domain Alignment [ICML2020]
- Margin-aware Adversarial Domain Adaptation with Optimal Transport [ICML2020] [code]
- Metric Learning in Optimal Transport for Domain Adaptation [IJCAI2020]
- Reliable Weighted Optimal Transport for Unsupervised Domain Adaptation [CVPR2020]
- Enhanced Transport Distance for Unsupervised Domain Adaptation [CVPR2020] [Pytorch]
- Differentially Private Optimal Transport: Application to Domain Adaptation [IJCAI2019]
- DeepJDOT: Deep Joint distribution optimal transport for unsupervised domain adaptation [ECCV2018] [Keras]
- Joint Distribution Optimal Transportation for Domain Adaptation [NIPS2017] [python] [Python Optimal Transport Library]
Arxiv
- CDOT: Continuous Domain Adaptation using Optimal Transport [20 Sep 2019]
Incremental Methods
- Incremental Unsupervised Domain-Adversarial Training of Neural Networks [TNNLS 2020]
Semi-Supervised-Learning-Based Methods
- Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation [ECCV2020]
- Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners [arXiv 2021][Pytorch]
Self-training-Based Methods
- Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark [ICCV Workshop 2021] [Pytorch]
- Instance Adaptive Self-Training for Unsupervised Domain Adaptation [ECCV 2020] [Pytorch]
- Self-training Avoids Using Spurious Features Under Domain Shift [NeurIPS 2020]
- Two-phase Pseudo Label Densification for Self-training based Domain Adaptation [ECCV2020]
Arxiv
- Probabilistic Contrastive Learning for Domain Adaptation [arXiv 20211] [Pytorch]
- Gradual Domain Adaptation via Self-Training of Auxiliary Models[arXiv 2021][Pytorch]
Self-Supervised Methods
Conference
- Self-Supervised CycleGAN for Object-Preserving Image-to-Image Domain Adaptation [ECCV2020]
Arxiv
- Unsupervised Domain Adaptation through Self-Supervision [arXiv 26 Sep 2019]
Other Methods
Conference
- A Prototype-Oriented Framework for Unsupervised Domain Adaptation [NeurIPS 2021] [Pytorch]
- Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift [NeurIPS 2020]
- Transferable Calibration with Lower Bias and Variance in Domain Adaptation [NeurIPS 2020]
- A Dictionary Approach to Domain-Invariant Learning in Deep Networks [NeurIPS 2020]
- Heuristic Domain Adaptation [NeurIPS2020] [Pytorch]
- Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images through Generative Latent Search [ECCV2020][code]
- Mind the Discriminability: Asymmetric Adversarial Domain Adaptation [ECCV2020]
- Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation [ECCV2020]
- CSCL: Critical Semantic-Consistent Learning for Unsupervised Domain Adaptation [ECCV2020]
- Minimum Class Confusion for Versatile Domain Adaptation [ECCV2020]
- Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift [ECCV2020] [Pytorch]
- Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation [ECCV2020] [PyTorch]
- Unsupervised Domain Adaptation via Structurally Regularized Deep Clustering [CVPR2020 Oral] [Pytorch]
- Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations [CVPR2020 Oral] [Pytorch]
- Unsupervised Domain Adaptation With Hierarchical Gradient Synchronization [CVPR2020]
- Spherical Space Domain Adaptation With Robust Pseudo-Label Loss [CVPR2020] [Pytorch]
- Stochastic Classifiers for Unsupervised Domain Adaptation [CVPR2020]
- Structure Preserving Generative Cross-Domain Learning [CVPR2020]
- Light-weight Calibrator: A Separable Component for Unsupervised Domain Adaptation [CVPR2020] [code]
- Domain Adaptive Multiflow Networks [ICLR2020]
- Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment [AAAI2020]
- Visual Domain Adaptation by Consensus-based Transfer to Intermediate Domain [Paper]
- Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling [AAAI2020] [Matlab]
- CUDA: Contradistinguisher for Unsupervised Domain Adaptation [ICDM2019]
- Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment [ICML2019]
- Batch Weight for Domain Adaptation With Mass Shift [ICCV2019]
- Switchable Whitening for Deep Representation Learning [ICCV2019] [pytorch]
- Confidence Regularized Self-Training [ICCV2019 Oral] [Pytorch]
- Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation [ICCV2019] [Pytorch(official)]
- Transferrable Prototypical Networks for Unsupervised Domain Adaptation [CVPR2019(Oral)]
- Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation [CVPR2019]
- Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss [CVPR 2019] [Pytorch]
- Domain Specific Batch Normalization for Unsupervised Domain Adaptation [CVPR2019] [Pytorch]
- AdaGraph: Unifying Predictive and Continuous Domain Adaptation through Graphs [CVPR2019] [Pytorch]
- Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach [CVPR2019] [Project]
- Contrastive Adaptation Network for Unsupervised Domain Adaptation [CVPR2019] [Pytorch]
- Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation [CVPR2019]
- Unsupervised Domain Adaptation via Calibrating Uncertainties [CVPRW2019]
- Bayesian Uncertainty Matching for Unsupervised Domain Adaptation [IJCAI2019]
- Unsupervised Domain Adaptation for Distance Metric Learning [ICLR2019]
- Co-regularized Alignment for Unsupervised Domain Adaptation [NIPS2018]
- Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation [TIP 2018]
- Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation [ECCV2018]
- Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation [CVPR2018]
- Unsupervised Domain Adaptation with Distribution Matching Machines [AAAI2018]
- Learning to cluster in order to transfer across domains and tasks [ICLR2018] [Bolg] [Pytorch]
- Self-Ensembling for Visual Domain Adaptation [ICLR2018]
- Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation [ICLR2018] [TensorFlow]
- Associative Domain Adaptation [ICCV2017] [TensorFlow] [Pytorch]
- AutoDIAL: Automatic DomaIn Alignment Layers [ICCV2017]
- Asymmetric Tri-training for Unsupervised Domain Adaptation [ICML2017] [TensorFlow]
- Learning Transferrable Representations for Unsupervised Domain Adaptation [NIPS2016]
Journal
- Target-Independent Domain Adaptation for WBC Classification using Generative Latent Search [IEEE TMI 2020][code]
- Adaptive Batch Normalization for practical domain adaptation [Pattern Recognition(2018)]
- Unsupervised Domain Adaptation by Mapped Correlation Alignment [IEEE ACCESS]
Arxiv
- Low-confidence Samples Matter for Domain Adaptation [6 Feb 2022] [Pytorch]
- Improving Unsupervised Domain Adaptation with Variational Information Bottleneck [21 Nov 2019]
- Deep causal representation learning for unsupervised domain adaptation [28 Oct 2019]
- Domain-invariant Learning using Adaptive Filter Decomposition [25 Sep 2019]
- Discriminative Clustering for Robust Unsupervised Domain Adaptation [arXiv 30 May 2019]
- Virtual Mixup Training for Unsupervised Domain Adaptation [arXiv on 24 May 2019] [Tensorflow]
- Learning Smooth Representation for Unsupervised Domain Adaptation [arXiv 26 May 2019]
- Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation [arXiv 13 Apr 2019]
- Easy Transfer Learning By Exploiting Intra-domain Structures [arXiv 2 Apr 2019]
- Domain Discrepancy Measure Using Complex Models in Unsupervised Domain Adaptation [arXiv 30 Jan 2019]
- Domain Alignment with Triplets [arXiv 22 Jan 2019]
- Deep Discriminative Learning for Unsupervised Domain Adaptation [arXiv 17 Nov 2018]
Semi-supervised DA
Conference
- Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation [CVPR2021]
- Improving Semi-Supervised Domain Adaptation Using Effective Target Selection and Semantics [CVPRW2021] [Code]
- Attract, Perturb, and Explore: Learning a Feature Alignment Network for Semi-supervised Domain Adaptation [ECCV2020]
- Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation [ECCV2020]
- Bidirectional Adversarial Training for Semi-Supervised Domain Adaptation [IJCAI2020]
- Semi-supervised Domain Adaptation via Minimax Entropy [ICCV2019] [Pytorch]
Arxiv
- MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation [ 24 Jul 2020]
- Opposite Structure Learning for Semi-supervised Domain Adaptation [6 Feb 2020]
- Reducing Domain Gap via Style-Agnostic Networks [25 Oct 2019]
Weakly-Supervised DA
Conference
- Towards Accurate and Robust Domain Adaptation under Noisy Environments [IJCAI2020]
- Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration [CVPR2019]
- Transferable Curriculum for Weakly-Supervised Domain Adaptation [AAAI2019]
Arxiv
- Butterfly: Robust One-step Approach towards Wildly-unsupervised Domain Adaptation [arXiv on 19 May 2019]
Zero-shot DA
Conference
- High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images [ECCV2020]
- Adversarial Learning for Zero-shot Domain Adaptation [ECCV2020]
- HGNet: Hybrid Generative Network for Zero-shot Domain Adaptation [ECCV2020]
- Zero-shot Domain Adaptation Based on Attribute Information [ACML2019]
- Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation [ICCV2019]
- Generalized Zero-Shot Learning with Deep Calibration Network [NIPS2018]
- Zero-Shot Deep Domain Adaptation [ECCV2018]
One-shot DA
Conference
- Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation [NeurIPS2020] [Pytorch]
- One-Shot Adaptation of Supervised Deep Convolutional Models [ICLR Workshop 2014]
Arxiv
- One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning [arxiv]
Few-shot UDA
Conference
- Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation [CVPR2021] [Pytorch] [Project]
Arxiv
- Cross-domain Self-supervised Learning for Domain Adaptation with Few Source Labels [arXiv 18 Mar 2020]
Few-shot DA
Conference
- Domain-Adaptive Few-Shot Learning[WACV2021] [Pytorch]
- Few-shot Domain Adaptation by Causal Mechanism Transfer [ICML2020] [Pytorch]
- Few-Shot Adaptive Faster R-CNN [CVPR2019]
- d-SNE: Domain Adaptation using Stochastic Neighborhood Embedding [CVPR2019 Oral]
- Few-Shot Adversarial Domain Adaptation [NIPS2017]
Partial DA
Conference
- A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation [ECCV2020] [Pytorch]
- Discriminative Partial Domain Adversarial Network [ECCV2020]
- Selective Transfer With Reinforced Transfer Network for Partial Domain Adaptation [CVPR2020]
- Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation [ACM MM2020]
- Multi-Weight Partial Domain Adaptation [BMVC2019]
- Learning to Transfer Examples for Partial Domain Adaptation [CVPR2019] [Pytorch]
- Partial Adversarial Domain Adaptation [ECCV2018] [Pytorch(Official)]
- Importance Weighted Adversarial Nets for Partial Domain Adaptation [CVPR2018] [Caffe]
- Partial Transfer Learning with Selective Adversarial Networks [CVPR2018][paper weekly] [Pytorch(Official) & Caffe(official)]
Journal
- Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]
Arxiv
- Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation [arXiv 06 Dec 2020]
- Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [20 Feb 2020] [PyTroch]
- Tackling Partial Domain Adaptation with Self-Supervision [arXiv 12 Jun 2019]
- Domain Adversarial Reinforcement Learning for Partial Domain Adaptation [arXiv 10 May 2019]
Open Set DA
Conference
- On the Effectiveness of Image Rotation for Open Set Domain Adaptation [ECCV2020] [Pytorch]
- Multi-Source Open-Set Deep Adversarial Domain Adaptation [ECCV2020]
- Progressive Graph Learning for Open-Set Domain Adaptation [ICML2020] [Pytorch]
- Joint Partial Optimal Transport for Open Set Domain Adaptation [IJCAI2020]
- Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation [CVPR2020]
- Towards Inheritable Models for Open-Set Domain Adaptation [CVPR 2020] [Project]
- Attract or Distract: Exploit the Margin of Open Set [ICCV2019] [code]
- Separate to Adapt: Open Set Domain Adaptation via Progressive Separation [CVPR2019] [Pytorch]
- Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration [CVPR2019]
- Learning Factorized Representations for Open-set Domain Adaptation [ICLR2019]
- Open Set Domain Adaptation by Backpropagation [ECCV2018] [Pytorch(Official)] [Tensorflow] [Pytorch]
- Open Set Domain Adaptation [ICCV2017]
Journal
- Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]
- Adversarial Network with Multiple Classifiers for Open Set Domain Adaptation [IEEE TMM] [Pytorch]
Arxiv
- Collaborative Training of Balanced Random Forests for Open Set Domain Adaptation [10 Feb 2020]
- Known-class Aware Self-ensemble for Open Set Domain Adaptation [3 May 2019]
Universal DA
Conference
- Active Universal Domain Adaptation [ICCV 2021]
- Domain Consensus Clustering for Universal Domain Adaptation [CVPR 2021] [Pytorch]
- Universal Domain Adaptation through Self Supervision [NeurIPS 2020] [Pytorch]
- Learning to Detect Open Classes for Universal Domain Adaptation [ECCV2020] [code]
- Universal Source-Free Domain Adaptation [CVPR2020] [Project]
- Universal Domain Adaptation [CVPR2019] [Pytorch]
Arxiv
- Universal Multi-Source Domain Adaptation [5 Nov 2020]
- A Sample Selection Approach for Universal Domain Adaptation [14 Jan 2020]
Open Compound DA
Conference
- Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation [NeurIPS2020]
- Open Compound Domain Adaptation [CVRP2020 Oral] [Pytorch]
Arxiv
- Source-Free Open Compound Domain Adaptation in Semantic Segmentation [arXiv]
Multi Source DA
Conference
- STEM: An approach to Multi-source Domain Adaptation with Guarantees [ICCV2021]
- MOST: Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning [UAI2021]
- Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark [ICCV Workshop 2021] [Pytorch]
- Your Classifier can Secretly Suffice Multi-Source Domain Adaptation [NeurIPS 2020] [Project]
- Multi-Source Open-Set Deep Adversarial Domain Adaptation [ECCV2020]
- Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation [ECCV2020]
- Multi-Source Open-Set Deep Adversarial Domain Adaptation [ECCV2020]
- Curriculum Manager for Source Selection in Multi-Source Domain Adaptation [ECCV2020]
- Domain Aggregation Networks for Multi-Source Domain Adaptation [ICML2020]
- Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation [ECCV2020] [Pytorch]
- Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits [AAAI2020]
- Multi-source Domain Adaptation for Visual Sentiment Classification [AAAI2020]
- Multi-source Distilling Domain Adaptation [AAAI2020] [code]
- Multi-source Domain Adaptation for Semantic Segmentation [NeurlPS2019] [Pytorch]
- Moment Matching for Multi-Source Domain Adaptation [ICCV2019] [Pytorch]
- Multi-Domain Adversarial Learning [ICLR2019] [Torch]
- Algorithms and Theory for Multiple-Source Adaptation [NIPS2018]
- Adversarial Multiple Source Domain Adaptation [NIPS2018] [Pytorch]
- Boosting Domain Adaptation by Discovering Latent Domains [CVPR2018] [Caffe] [Pytorch]
- Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift [CVPR2018] [Pytorch]
Journal
- A survey of multi-source domain adaptation [Information Fusion]
Arxiv
- Domain Adaptive Ensemble Learning [arXiv]
- Multi-Source Domain Adaptation and Semi-Supervised Domain Adaptation with Focus on Visual Domain Adaptation Challenge 2019 [14 Oct 2019]
Multi Target DA
- Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach [arXiv]
Incremental DA
Conference
- Learning to Adapt to Evolving Domains [NeurIPS 2020] [Pytorch]
- Class-Incremental Domain Adaptation [ECCV2020]
- Incremental Adversarial Domain Adaptation for Continually Changing Environments [ICRA2018]
- Continuous Manifold based Adaptation for Evolving Visual Domains [CVPR2014]
Multi Step DA
Arxiv
- Adversarial Domain Adaptation for Stance Detection [arXiv]
- Ensemble Adversarial Training: Attacks and Defenses [arXiv]
Conference
- Distant domain transfer learning [AAAI2017]
Heterogeneous DA
Conference
- Domain Adaptive Classification on Heterogeneous Information Networks [IJCAI2020]
- Heterogeneous Domain Adaptation via Soft Transfer Network [ACM MM2019]
Target-agnostic DA
Arxiv
- Compound Domain Adaptation in an Open World [8 Sep 2019]
Conference
- Domain Agnostic Learning with Disentangled Representations [ICML2019] [Pytorch]
- Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks [CVPR2019] [Pytorch]
Federated DA
Arxiv
- Federated Adversarial Domain Adaptation [5 Nov 2019]
Continuously Indexed DA
Conference
- Continuously Indexed Domain Adaptation [ICML 2020] [Pytorch] [Project Page] [Video]
Source Free DA
Conference
- Confident Anchor-Induced Multi-Source Free Domain Adaptation [NeurIPS2021] [Pytorch]
- Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data [NeurIPS2021] [Pytorch]
- Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation [NeurIPS2021] [Pytorch]
- Unsupervised Domain Adaptation of Black-Box Source Models [BMVC2021][Pytorch]
- Generalize Then Adapt: Source-Free Domain Adaptive Semantic Segmentation [ICCV2021] [Project]
- Generalized Source-free Domain Adaptation [ICCV2021] [Pytorch]
- Adaptive Adversarial Network for Source-free Domain Adaptation [ICCV2021] [Pytorch]
- Visualizing Adapted Knowledge in Domain Transfer [CVPR2021] [Pytorch]
- Unsupervised Multi-source Domain Adaptation Without Access to Source Data [CVPR2021] [Pytorch]
- Source-Free Domain Adaptation for Semantic Segmentation [CVPR2021]
- Domain Impression: A Source Data Free Domain Adaptation Method [WACV2021] [Project]
- Model Adaptation: Unsupervised Domain Adaptation Without Source Data [CVPR2020]
- Universal Source-Free Domain Adaptation [CVPR2020] [Project]
- Towards Inheritable Models for Open-Set Domain Adaptation [CVPR2020] [Project]
- Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation [ICML2020] [Pytorch]
Arxiv
- Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis Transfer[7 Jul 2021][Pytorch]
- Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer [14 Dec 2020] [Pytorch]
Model Selection
- The Balancing Principle for Parameter Choice in Distance-Regularized Domain Adaptation [NeurIPS2021] [Pytorch]
- Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation [ICML2019] [Pytorch]
Other Transfer Learning Paradigms
Domain Generalization
Conference
- Domain Generalization via Inference-time Label-Preserving Target Projections [CVPR2021] [Pytorch]
- Domain Generalization via Entropy Regularization [NeurIPS2020] [Pytorch]
- Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization [NeurIPS2020]
- Learning to Learn with Variational Information Bottleneck for Domain Generalization [ECCV2020]
- Self-Challenging Improves Cross-Domain Generalization [ECCV2020] [Pytorch]
- Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization [ECCV2020] [Pytorch]
- Learning to Balance Specificity and Invariance for In and Out of Domain Generalization [ECCV2020] [Pytorch]
- Learning to Generate Novel Domains for Domain Generalization [ECCV2020]
- Learning to Optimize Domain Specific Normalization for Domain Generalization [ECCV2020]
- Towards Recognizing Unseen Categories in Unseen Domains [ECCV2020] [Pytorch]
- Efficient Domain Generalization via Common-Specific Low-Rank Decomposition [ICML2020] [Pytorch]
- Learning to Learn Single Domain Generalization [CVPR2020] [Pytorch]
- Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition [ICLR2020]
- Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation [ICLR2020]
- Domain Generalization Using a Mixture of Multiple Latent Domains [AAAI2020] [Pytorch]
- Deep Domain-Adversarial Image Generation for Domain Generalisation [Paper] [Pytorch]
- Domain Generalization via Model-Agnostic Learning of Semantic Features [NeurIPS2019] [Tensorflow]
- Episodic Training for Domain Generalization [ICCV2019 Oral] [Pytorch]](https://github.com/HAHA-DL/Episodic-DG)
- Feature-Critic Networks for Heterogeneous Domain Generalization [ICML2019] [Pytorch]
- Domain Generalization by Solving Jigsaw Puzzles [CVPR2019 Oral] [Pytorch]
- MetaReg: Towards Domain Generalization using Meta-Regularization [NIPS2018]
- Deep Domain Generalization via Conditional Invariant Adversarial Networks [ECCV2018]
- Domain Generalization with Adversarial Feature Learning [CVPR2018]
Journal
- Domain Generalization for Regression [IntellManuf2020]
- Correlation-aware Adversarial Domain Adaptation and Generalization [Pattern Recognition(2019)] [code]
Arxiv
- Adversarial Pyramid Network for Video Domain Generalization [8 Dec 2019]
- Towards Shape Biased Unsupervised Representation Learning for Domain Generalization [18 Sep 2019]
- A Generalization Error Bound for Multi-class Domain Generalization [24 May 2019]
- Adversarial Invariant Feature Learning with Accuracy Constraint for Domain Generalization [29 Apr 2019]
- Beyond Domain Adaptation: Unseen Domain Encapsulation via Universal Non-volume Preserving Models [9 Dec 2018]
Domain Randomization
Conference
- DeceptionNet: Network-Driven Domain Randomization [ICCV2019]
- Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization Without Accessing Target Domain Data [ICCV2019]
Transfer Metric Learning
- Transfer Metric Learning: Algorithms, Applications and Outlooks [arXiv]
Knowledge Transfer
Conference
- Attention Bridging Network for Knowledge Transfer [ICCV2019]
- Few-Shot Image Recognition with Knowledge Transfer [ICCV2019]
Others
Conference
- Learning Across Tasks and Domains [ICCV2019]
- UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation [ICCV2019]
- Domain Agnostic Learning with Disentangled Representations [ICML2019]
- Unsupervised Open Domain Recognition by Semantic Discrepancy Minimization [CVPR2019] [Pytorch]
Arxiv
- GradMix: Multi-source Transfer across Domains and Tasks [[9 Feb 2020]](GradMix: Multi-source Transfer across Domains and Tasks)
- When Semi-Supervised Learning Meets Transfer Learning: Training Strategies, Models and Datasets [arXiv 13 Dec 2018]
Applications
Object Detection
Survey
- Unsupervised Domain Adaptation of Object Detectors: A Survey [Arxiv 27 May 2021]
Conference
- Dual Bipartite Graph Learning: A General Approach for Domain Adaptive Object Detection [ICCV2021]
- Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection [ICCV2021]
- MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection [CVPR2021]
- I3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors [CVPR2021]
- RPN Prototype Alignment for Domain Adaptive Object Detector [CVPR2021]
- Domain-Specific Suppression for Adaptive Object Detection [CVPR2021]
- Unbiased Mean Teacher for Cross-Domain Object Detection [CVPR2021]
- YOLO in the Dark - Domain Adaptation Method for Merging Multiple Models [ECCV2020]
- Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection [ECCV2020]
- One-Shot Unsupervised Cross-Domain Detection [ECCV2020]
- Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector [ECCV2020]
- Adapting Object Detectors with Conditional Domain Normalization [ECCV2020]
- Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions [ECCV2020]
- Domain Adaptive Object Detection via Asymmetric Tri-way Faster-RCNN [ECCV2020]
- Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation [CVPR2020]
- Harmonizing Transferability and Discriminability for Adapting Object Detectors [CVPR2020] [code]
- Exploring Categorical Regularization for Domain Adaptive Object Detection [CVPR2020] [code]
- Cross-domain Detection via Graph-induced Prototype Alignment [CVPR2020 Oral] [code]
- Multi-spectral Salient Object Detection by Adversarial Domain Adaptation [Paper]
- Deep Domain Adaptive Object Detection: a Survey [ICIP2020]
- Progressive Domain Adaptation for Object Detection [WACV]
- Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night [IJCNN2019 Oral] [Project]
- Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection [ICCV2019 Oral]
- A Robust Learning Approach to Domain Adaptive Object Detection [ICCV2019] [code]
- Multi-adversarial Faster-RCNN for Unrestricted Object Detection [ICCV2019]
- Few-Shot Adaptive Faster R-CNN [CVPR2019]
- Exploring Object Relation in Mean Teacher for Cross-Domain Detection [CVPR2019]
- Adapting Object Detectors via Selective Cross-Domain Alignment [CVPR2019] [Pytorch]
- Automatic adaptation of object detectors to new domains using self-training [CVPR2019] [Project]
- Towards Universal Object Detection by Domain Attention [CVPR2019]
- Strong-Weak Distribution Alignment for Adaptive Object Detection [CVPR2019] [Pytorch]
- Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection [CVPR2019] [Pytorch]
- Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation [CVPR2018]
- Domain Adaptive Faster R-CNN for Object Detection in the Wild [CVPR2018] [Caffe2] [Caffe] [Pytorch(under developing)]
Journal
- Cross-domain object detection using unsupervised image translation [ESWA]
- Pixel and feature level based domain adaptation for object detection in autonomous driving [Neurocomputing]
Arxiv
- See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation [17 Nov 2021]
- Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation [3 Feb 2020]
- Prior-based Domain Adaptive Object Detection for Adverse Weather Conditions [29 Nov 2019]
- Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning [17 Nov 2019]
- Curriculum Self-Paced Learning for Cross-Domain Object Detection [15 Nov 2019]
- SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses [6 Nov 2019]
Semantic Segmentation
Conference
- Generalize Then Adapt: Source-Free Domain Adaptive Semantic Segmentation [ICCV2021] [Project]
- Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation [CVPR2021] [Pytorch]
- Instance Adaptive Self-Training for Unsupervised Domain Adaptation [ECCV 2020] [Pytorch]
- Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning [ICASSP 2020]
- Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation [NeurlIPS 2020] [Pytorch]
- Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation [NeurIPS2020] [Pytorch]
- Semantically Adaptive Image-to-image Translation for Domain Adaptation of Semantic Segmentation [BMVC2020]
- Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation [ECCV2020]
- Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation [ECCV2020]
- Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation [ECCV2020]
- Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images through Generative Latent Search [ECCV2020]
- Domain Adaptive Semantic Segmentation Using Weak Labels [ECCV2020]
- Content-Consistent Matching for Domain Adaptive Semantic Segmentation [ECCV2020] [PyTorch]
- Cross-Domain Semantic Segmentation via Domain-Invariant Interactive Relation Transfer [CVPR2020]
- Phase Consistent Ecological Domain Adaptation [CVPR2020] [Pytorch]
- FDA: Fourier Domain Adaptation for Semantic Segmentation [CVPR2020] [Pytorch]
- Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting [CVPR2020]
- Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision [CVPR2020 Oral] [Pytorch]
- Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation [CVPR2020]
- Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation [CVPR2020] [Pytorch]
- xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation [CVPR2020] [Demo] [code]
- Unsupervised Scene Adaptation with Memory Regularization in vivo [IJCAI2020] [code]
- Joint Adversarial Learning for Domain Adaptation in Semantic Segmentation [AAAI2020]
- An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation [AAAI2020]
- Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation [NeurIPS2019] [code]
- MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with Spatially Independent and Semantically Consistent Labeling [WACV2020]
- Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation [WACV2020]
- Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation [ICCV2019]
- Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach [ICCV2019] [Pytorch]
- SSF-DAN: Separated Semantic Feature Based Domain Adaptation Network for Semantic Segmentation [ICCV2019]
- Significance-aware Information Bottleneck for Domain Adaptive Semantic Segmentation [ICCV2019]
- Domain Adaptation for Semantic Segmentation with Maximum Squares Loss [ICCV2019] [Pytorch]
- Self-Ensembling with GAN-based Data Augmentation for Domain Adaptation in Semantic Segmentation [ICCV2019]
- DADA: Depth-aware Domain Adaptation in Semantic Segmentation [ICCV2019] [code]
- Domain Adaptation for Structured Output via Discriminative Patch Representations [ICCV2019 Oral] [Project]
- Not All Areas Are Equal: Transfer Learning for Semantic Segmentation via Hierarchical Region Selection [CVPR2019(Oral)]
- CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency [CVPR2019] [Project] [Pytorch]
- Bidirectional Learning for Domain Adaptation of Semantic Segmentation [CVPR2019] [Pytorch]
- Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach [CVPR2019]
- All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation [CVPR2019] [Pytorch]
- DLOW: Domain Flow for Adaptation and Generalization [CVPR2019 Oral]
- Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation [CVPR2019 Oral] [Pytorch]
- ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation [CVPR2019 Oral] [Pytorch]
- SPIGAN: Privileged Adversarial Learning from Simulation [ICLR2019]
- Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation [ECCV2018]
- Domain transfer through deep activation matching [ECCV2018]
- Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training [ECCV2018] [Pytorch]
- DCAN: Dual channel-wise alignment networks for unsupervised scene adaptation [ECCV2018]
- Fully convolutional adaptation networks for semantic segmentation [CVPR2018]
- Learning to Adapt Structured Output Space for Semantic Segmentation [CVPR2018] [Pytorch]
- Conditional Generative Adversarial Network for Structured Domain Adaptation [CVPR2018]
- Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation [CVPR2018] [Pytorch]
- Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes [ICCV2017] [Journal Version] [Keras]
- No more discrimination: Cross city adaptation of road scene segmenters [ICCV2017]
Journal
- Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation [IJCV2020][Pytorch]
- Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet [Neurocomputing 2021] [Pytorch]
- Affinity Space Adaptation for Semantic Segmentation Across Domains [TIP2020][Pytorch]
- Semantic-aware short path adversarial training for cross-domain semantic segmentation [Neurocomputing 2019]
- Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes [TIP]
Arxiv
- Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene Segmentation [29 Mar 2021][Pytorch]
- Class-Conditional Domain Adaptation on Semantic Segmentation [27 Nov 2019]
- Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation [2 Sep 2019]
- FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation [8 Dec 2016]
- BoMuDA: Boundless Multi-Source Domain Adaptive Segmentation in Unconstrained Environments [13 Oct 2020][Pytorch]
- SAfE: Self-Attention Based Unsupervised Road Safety Classification in Hazardous Environments [27 Nov 2020][Pytorch]
- Semantics-aware Multi-modal Domain Translation:From LiDAR Point Clouds to Panoramic Color Images [26 Jun 2021] [Pytorch]
Person Re-identification
Conference
- Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification [ECCV2020]
- Joint Visual and Temporal Consistency for Unsupervised Domain Adaptive Person Re-Identification [ECCV2020]
- Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification [ECV2020]
- Multiple Expert Brainstorming for Domain Adaptive Person Re-identification [ECCV2020]
- Deep Credible Metric Learning for Unsupervised Domain Adaptation Person Re-identification [ECCV2020]
- Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification [ECCV2020]
- Generalizing Person Re-Identification by Camera-Aware Invariance Learning and Cross-Domain Mixup [ECCV2020]
- AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification [CVPR2020]
- Smoothing Adversarial Domain Attack and P-Memory Reconsolidation for Cross-Domain Person Re-Identification [CVPR2020]
- Cross-Modal Cross-Domain Moment Alignment Network for Person Search [CVPR2020]
- Online Joint Multi-Metric Adaptation From Frequent Sharing-Subset Mining for Person Re-Identification [CVPR2020]
- Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification [ICLR2020] [Pytorch]
- Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification [ICCV2019 Oral] [Pytorch]
- A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification [ICCV2019]
- Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification [CVPR2019] [Pytorch]
- Domain Adaptation through Synthesis for Unsupervised Person Re-identification [ECCV2018]
- Person Transfer GAN to Bridge Domain Gap for Person Re-Identification [CVPR2018]
- Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification [CVPR2018]
Arxiv
- Domain Adaptation for Semantic Segmentation via Patch-Wise Contrastive Learning [arXiv 22 Apr 2021]
- Structured Domain Adaptation for Unsupervised Person Re-identification [arXiv 14 Mar 2020]
- Domain Adaptive Attention Model for Unsupervised Cross-Domain Person Re-Identification [arXiv 25 May 2019]
- Camera Adversarial Transfer for Unsupervised Person Re-Identification [arXiv 2 Apr 2019]
- EANet: Enhancing Alignment for Cross-Domain Person Re-identification [arXiv 29 Dec 2018] [Pytorch]
- One Shot Domain Adaptation for Person Re-Identification [arXiv 26 Nov 2018]
- Similarity-preserving Image-image Domain Adaptation for Person Re-identification [arXiv 26 Nov 2018]
Sim-to-Real Transfer
Conference
- DIRL: Domain-Invariant Reperesentation Learning Approach for Sim-to-Real Transfer [CoRL2020] [Project]
Video Domain Adaptation
Conference
- Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing [NeurIPS2021]
- Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network [ICCV2021]
- Shuffle and Attend: Video Domain Adaptation [ECCV2020]
- Transferring Cross-Domain Knowledge for Video Sign Language Recognition [CVPR2020]
- Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation [CVPR2020] [Pytorch]
- Transferring Cross-domain Knowledge for Video Sign Language Recognition [CVPR2020 Oral]
- Multi-Modal Domain Adaptation for Fine-Grained Action Recognition [CVPR2020 Oral]
- Adversarial Cross-Domain Action Recognition with Co-Attention [AAAI2020]
- Generative Adversarial Networks for Video-to-Video Domain Adaptation [Paper]
- Temporal Attentive Alignment for Large-Scale Video Domain Adaptation [ICCV2019 Oral] [Pytorch]
- Temporal Attentive Alignment for Video Domain Adaptation [CVPRW 2019] [Pytorch]
Arxiv
- Image to Video Domain Adaptation Using Web Supervision [5 Aug 2019]
Medical Related
Conference
- Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning [ICASSP 2020]
- What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation [Paper]
- Semantic-Transferable Weakly-Supervised Endoscopic Lesions Segmentation [ICCV2019]
Journal
- Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet [Neurocomputing 2021] [Pytorch]
Arxiv
- Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation [arXiv 29 Aug 2019]
- Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation [arXiv on 24 Jan 2019]
- Unsupervised domain adaptation for medical imaging segmentation with self-ensembling [arXiv 14 Nov 2018]
Monocular Depth Estimation
- Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation [CVPR2019]
- Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer [CVPR2018]
3D Reconstruction
Conference
- Domain-Adaptive Single-View 3D Reconstruction [ICCV2019]
Fine-Grained Domain
Conference
- Progressive Adversarial Networks for Fine-Grained Domain Adaptation [CVPR2020] [Pytorch]
LiDAR
ArXiv
- ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation [13 Mar 2022]
Others
Conference
- Unsupervised Domain Adaptation in LiDAR Semantic Segmentation with Self-Supervision and Gated Adapters [ICRA2022]
- Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark [ICCV Workshop 2021] [Pytorch]
- Adapting Neural Architectures Between Domains [NeurlPS 2020]
- Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition [ECCV2020]
- A Broader Study of Cross-Domain Few-Shot Learning [ECCV2020]
- Label-Noise Robust Domain Adaptation [ICML2020]
- Unsupervised Domain Adaptation of a Pretrained Cross-Lingual Language Model [IJCAI2020]
- Domain Adaptation for Semantic Parsing [IJCAI2020]
- Bridging Cross-Tasks Gap for Cognitive Assessment via Fine-Grained Domain Adaptation [IJCAI2020]
- Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation [IJCAI2020]
- Weakly-Supervised Domain Adaptation via GAN and Mesh Model for Estimating 3D Hand Poses Interacting Objects [CVPR2020]
- One-Shot Domain Adaptation for Face Generation [CVPR2020]
- Learning Meta Face Recognition in Unseen Domains [CVPR2020 Oral] [code]
- Cross-Domain Document Object Detection: Benchmark Suite and Method [CVPR2020] [code]
- StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo Matching [CVPR2020]
- Domain Adaptation for Image Dehazing [CVPR2020]
- Probability Weighted Compact Feature for Domain Adaptive Retrieval [CVPR2020] [code]
- Disparity-Aware Domain Adaptation in Stereo Image Restoration [CVPR2020]
- Multi-Path Learning for Object Pose Estimation Across Domains [CVPR2020]
- Unsupervised Domain Adaptation for 3D Human Pose Estimation [ACM MM2019]
- PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation [NeurIPS 2019] [code]
- Deep Head Pose Estimation Using Synthetic Images and Partial Adversarial Domain Adaption for Continuous Label Spaces [ICCV2019]
- Cross-Domain Adaptation for Animal Pose Estimation [ICCV2019]
- GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition [ICCV2019]
- Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning [IJCNN]
- Adversarial Adaptation of Scene Graph Models for Understanding Civic Issues [WWW2019]
- Cross-Dataset Adaptation for Visual Question Answering [CVPR2018]
Journal
- DASGIL: Domain Adaptation for Semantic and Geometric-Aware Image-Based Localization [TIP2020] [Pytorch]
- An Unsupervised Domain Adaptation Scheme for Single-Stage Artwork Recognition in Cultural Sites [Image and Vision Computing 2020] [Pytorch] [Project]
- Multi-source transfer learning of time series in cyclical manufacturing [JIntellManuf2020]
- Domain adaptation for regression under Beer-Lambert's law [KBS2020]
Arxiv
- Open-Ended Visual Question Answering by Multi-Modal Domain Adaptation [11 Nov 2019]
- DANE: Domain Adaptive Network Embedding [arXiv 3 Jun 2019]
- Active Adversarial Domain Adaptation [arXiv 16 Apr 2019]
Related Topics
Image-to-Image Translation
Arxiv
- MISO: Mutual Information Loss with Stochastic Style Representations for Multimodal Image-to-Image Translation [arXiv 11 Feb 2019]
- TraVeLGAN: Image-to-image Translation by Transformation Vector Learning [arXiv 25 Feb 2019]
Conference
- LLVIP: A Visible-infrared Paired Dataset for Low-light Vision [ICCV Workshop 2021] [Pytorch]
- Batch Weight for Domain Adaptation With Mass Shift [ICCV2019]
- Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer [ICLR2019] [Pytorch]
- Unsupervised Attention-guided Image-to-Image Translation [NIPS2018]
- Image-to-image translation for cross-domain disentanglement [NIPS2018]
- One-Shot Unsupervised Cross Domain Translation [NIPS2018]
- A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation [NIPS2018]
- Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound [NIPS2018]
- Multi-view Adversarially Learned Inference for Cross-domain Joint Distribution Matching [KDD2018]
- Unpaired Multi-Domain Image Generation via Regularized Conditional GANs [IJCAI2018] [TensorFlow]
- Improving Shape Deformation in Unsupervised Image-to-Image Translation [ECCV2018]
- NAM: Non-Adversarial Unsupervised Domain Mapping [ECCV2018]
- AugGAN: Cross Domain Adaptation with GAN-based Data Augmentation [ECCV2018]
- Recycle-GAN: Unsupervised Video Retargeting [ECCV2018] [Project]
- Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks [ECCV2018]
- Diverse Image-to-Image Translation via Disentangled Representations [ECCV2018] [Pytorch(Official)] [Tensorflow]
- Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation [ECCV2018]
- Multimodal Unsupervised Image-to-Image Translation [ECCV2018] [Pytorch(Official)]
- JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets [ICML2018] [TensorFlow(Official)]
- DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks [CVPR2018]
- StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation [CVPR2018] [Pytorch(Official)]
- Conditional Image-to-Image Translation [CVPR2018]
- Toward Multimodal Image-to-Image Translation [NIPS2017] [Project] [Pyotorch(Official)]
- Unsupervised Image-to-Image Translation Networks [NIPS2017] [Pytorch(Official)]
- Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks [ICCV2017(extended version)] [Pytorch(Official)]
- Image-to-Image Translation with Conditional Adversarial Nets [CVPR2017] [Project] [Pytorch(Official)]
- Learning to Discover Cross-Domain Relations with Generative Adversarial Networks [ICML2017] [Pytorch(Official)]
- Unsupervised Cross-Domain Image Generation [ICLR2017 Poster] [TensorFlow]
- Coupled Generative Adversarial Networks [NIPS2016] [Pytorch(Official)]
Disentangled Representation Learning
Arxiv
- Towards a Definition of Disentangled Representations [arXiv 5 Dec 2018]
Conference
- Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer [ICLR2019] [Pytorch]
- Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies [NIPS2018]
- Image-to-image translation for cross-domain disentanglement [NIPS2018]
Benchmarks
- Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark [ICCV Workshop 2021] [Pytorch]
- LLVIP: A Visible-infrared Paired Dataset for Low-light Vision [ICCV Workshop 2021] [Pytorch]
- Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation [arXiv 26 Jun] [Project]
- Benchmarking Neural Network Robustness to Common Corruptions and Perturbations (ImageNet-C) [ICLR 2019] [PyTorch]
Library
- Transfer-Learning-Library
- deep-transfer-learning: a PyTorch library for deep transfer learning
- salad: a Semi-supervised Adaptive Learning Across Domains
- Dassl: a PyTorch toolbox for domain adaptation and semi-supervised learning
Lectures and Tutorials
- A Primer on Domain Adaptation [PDF]
Other Resources
原文:https://github.com/zhaoxin94/awesome-domain-adaptation
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