awesome-domain-adaptation

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
    • Adversarial Methods
    • Distance-based Methods
    • Information-based Methods
    • Optimal Transport
    • Incremental Methods
    • Semi-Supervised-Learning-Based Methods
    • Self-training-Based Methods
    • Other Methods
  • Semi-supervised DA
  • Weakly-Supervised DA
  • Zero-shot DA
  • One-shot DA
  • 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
    • Domain Generalization
    • Domain Randomization
    • Transfer Metric Learning
    • Knowledge Transfer
    • Others
  • Applications
    • Object Detection
    • Semantic Segmentation
    • Person Re-identification
    • Sim-to-Real Transfer
    • Video Domain Adaptation
    • Medical Related
    • Monocular Depth Estimation
    • 3D Reconstruction
    • Fine-Grained Domain
    • Others
  • Related Topics
    • Image-to-Image Translation
    • Disentangled Representation Learning
  • Benchmarks
• Library
• Lectures and Tutorials
• Other Resources

Papers

Survey

Arxiv

• 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

• 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

• 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]
• 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

• 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]

Self-training-Based Methods

• Self-training Avoids Using Spurious Features Under Domain Shift [NeurIPS 2020]
• Two-phase Pseudo Label Densification for Self-training based Domain Adaptation [ECCV2020]

Other Methods

Conference

• 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]
• 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]
• Self-Supervised CycleGAN for Object-Preserving Image-to-Image 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

• Adaptive Batch Normalization for practical domain adaptation [Pattern Recognition(2018)]
• Unsupervised Domain Adaptation by Mapped Correlation Alignment [IEEE ACCESS]

Arxiv

• 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]
• 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 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]
• 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

• 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 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

• Visualizing Adapted Knowledge in Domain Transfer [CVPR2021] [Pytorch]
• 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

• Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer [14 Dec 2020] [Pytorch]
• Unsupervised Domain Adaptation of Black-Box Source Models [28 Mar 2021]

Model Selection

• 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]
• Domain Generalization via Entropy Regularization [NeurIPS2020]
• 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] [code]
• Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization [ECCV2020]
• Learning to Balance Specificity and Invariance for In and Out of Domain Generalization [ECCV2020]
• 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]
• Efficient Domain Generalization via Common-Specific Low-Rank Decomposition [ICML2020] [Pytorch]
• Learning to Learn Single Domain Generalization [CVPR2020] [code]
• 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] [code]
• 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

• 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

Conference

• 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

• Pixel and feature level based domain adaptation for object detection in autonomous driving [Neurocomputing]

Arxiv

• 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

• Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation [CVPR2021] [Pytorch]
• 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]
• 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]
• 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]

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

• 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

• 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

• What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation [Paper]
• Semantic-Transferable Weakly-Supervised Endoscopic Lesions Segmentation [ICCV2019]

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]

Others

Conference

• 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

• 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

• 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

• transferlearning