This repo is a collection of AWESOME things about domain adaptation, including papers, code, etc. Feel free to star and fork.
- awsome-domain-adaptation
- Contents
- Papers
- Survey
- Theory
- Unsupervised DA
- Semi-supervised DA
- Weakly-Supervised DA
- Zero-shot DA
- One-shot DA
- Few-shot DA
- Open Set DA
- Partial DA
- Multi Source DA
- Multi Target DA
- Multi Step DA
- Heterogeneous DA
- Target-agnostic DA
- Source-agnostic DA
- Federated DA
- Model Selection
- Other Transfer Learning Paradigms
- Applications
- Related Topics
- Benchmarks
- Library
- Other Resources
- Transfer Adaptation Learning: A Decade Survey [arXiv 12 Mar 2019]
- A review of single-source unsupervised domain adaptation [arXiv 16 Jan 2019]
- An introduction to domain adaptation and transfer learning [arXiv 31 Dec 2018]
- A Survey of Unsupervised Deep Domain Adaptation [arXiv 6 Dec 2018]
- A Survey on Deep Transfer Learning [ICANN2018]
- Deep Visual Domain Adaptation: A Survey [arXiv 2018]
- Transfer Learning for Cross-Dataset Recognition: A Survey [arXiv 2017]
- Domain Adaptation for Visual Applications: A Comprehensive Survey [arXiv 2017]
- Visual domain adaptation: A survey of recent advances [2015]
Arxiv
- A General Upper Bound for Unsupervised Domain Adaptation [3 Oct 2019]
- On Deep Domain Adaptation: Some Theoretical Understandings [arXiv 15 Nov 2018]
Conference
- Bridging Theory and Algorithm for Domain Adaptation [ICML2019] [Pytorch]
- On Learning Invariant Representation for Domain Adaptation [ICML2019] [code]
- Learning Bounds for Domain Adaptation [NIPS2007]
- Analysis of Representations for Domain Adaptation [NIPS2006]
Journal
- A theory of learning from different domains [ML2010]
Arxiv
- 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]
Conference
- Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition [IJCNN2019] [Matlab]
- Transfer Learning with Dynamic Adversarial Adaptation Network [ICDM2019]
- Cycle-consistent Conditional Adversarial Transfer Networks [ACM MM2019] [Pytorch]
- Learning Disentangled Semantic Representation for Domain Adaptation [IJCAI2019]
- 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]
- Universal Domain Adaptation [CVPR2019] [Pytorch]
- 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]
- 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
- TarGAN: Generating target data with class labels for unsupervised domain adaptation [Knowledge-Based Systems]
Arxiv
- Deep Domain Confusion: Maximizing for Domain Invariance [Arxiv 2014]
Conference
- 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]
- Deep CORAL: Correlation Alignment for Deep Domain Adaptation [ECCV2016]
- CDOT: Continuous Domain Adaptation using Optimal Transport [20 Sep 2019]
- Differentially Private Optimal Transport: Application to Domain Adaptation [IJCAI]
- 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]
- Incremental Adversarial Domain Adaptation for Continually Changing Environments [ICRA2018]
- Continuous Manifold based Adaptation for Evolving Visual Domains [CVPR2014]
Arxiv
- 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]
Conference
- 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]
- 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]
- 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]
- 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
- Reducing Domain Gap via Style-Agnostic Networks [25 Oct 2019]
Conference
- Semi-supervised Domain Adaptation via Minimax Entropy [ICCV2019] [Pytorch]
Arxiv
- Butterfly: Robust One-step Approach towards Wildly-unsupervised Domain Adaptation [arXiv on 19 May 2019]
Conference
- Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration [CVPR2019]
- Transferable Curriculum for Weakly-Supervised Domain Adaptation [AAAI2019]
Arxiv
- Zero-shot Domain Adaptation Based on Attribute Information [arXiv 13 Mar 2019]
Conference
- 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 Imitation from Observing Humans via Domain-Adaptive Meta-Learning [arxiv]
- One-Shot Adaptation of Supervised Deep Convolutional Models [ICLR Workshop 2014]
- d-SNE: Domain Adaptation using Stochastic Neighborhood Embedding [CVPR2019 Oral]
- Few-Shot Adversarial Domain Adaptation [NIPS2017]
Arxiv
- Known-class Aware Self-ensemble for Open Set Domain Adaptation [arXiv 3 May 2019]
Conference
- Separate to Adapt: Open Set Domain Adaptation via Progressive Separation [CVPR2019]
- 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]
Arxiv
- Tackling Partial Domain Adaptation with Self-Supervision [arXiv 12 Jun 2019]
- Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation [arXiv 26 May 2019]
- Domain Adversarial Reinforcement Learning for Partial Domain Adaptation [arXiv 10 May 2019]
Conference
- Learning to Transfer Examples for Partial Domain Adaptation [CVPR2019]
- Partial Adversarial Domain Adaptation [ECCV2018] [Pytorch(Official)]
- Importance Weighted Adversarial Nets for Partial Domain Adaptation [CVPR2018]
- Partial Transfer Learning with Selective Adversarial Networks [CVPR2018][paper weekly] [Pytorch(Official) & Caffe(official)]
Arxiv
- Multi-Source Domain Adaptation and Semi-Supervised Domain Adaptation with Focus on Visual Domain Adaptation Challenge 2019 [14 Oct 2019]
Conference
- Multi-source Domain Adaptation for Semantic Segmentation [NeurlPS2019]
- Moment Matching for Multi-Source Domain Adaptation [ICCV2019] [Pytorch]
- Multi-Domain Adversarial Learning [ICLR2019]
- Algorithms and Theory for Multiple-Source Adaptation [NIPS2018]
- Adversarial Multiple Source Domain Adaptation [NIPS2018] [Pytorch]
- Boosting Domain Adaptation by Discovering Latent Domains [CVPR2018]
- Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift [CVPR2018] [Pytorch]
Journal
- A survey of multi-source domain adaptation [Information Fusion]
- Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach [arXiv]
Arxiv
- Adversarial Domain Adaptation for Stance Detection [arXiv]
- Ensemble Adversarial Training: Attacks and Defenses [arXiv]
Conference
- Distant domain transfer learning [AAAI2017]
- Heterogeneous Domain Adaptation via Soft Transfer Network [ACM MM2019]
Arxiv
- Compound Domain Adaptation in an Open World [8 Sep 2019]
Conference
- Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks [CVPR2019] [Pytorch]
- Domain Agnostic Learning with Disentangled Representations [ICML2019] [Pytorch]
Arxiv
- Federated Adversarial Domain Adaptation [5 Nov 2019]
- Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation [ICML2019] [Pytorch]
Arxiv
- 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]
Conference
- Domain Generalization via Model-Agnostic Learning of Semantic Features [NeurIPS2019]
- 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]
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: Algorithms, Applications and Outlooks [arXiv]
Conference
- Attention Bridging Network for Knowledge Transfer [ICCV2019]
- Few-Shot Image Recognition with Knowledge Transfer [ICCV2019]
Arxiv
- When Semi-Supervised Learning Meets Transfer Learning: Training Strategies, Models and Datasets [arXiv 13 Dec 2018]
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
- SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses [6 Nov 2019]
Conference
- 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]
- Exploring Object Relation in Mean Teacher for Cross-Domain Detection [CVPR2019]
- Adapting Object Detectors via Selective Cross-Domain Alignment [CVPR2019]
- 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]
- 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
- Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation [23 Oct 2019]
- Restyling Data: Application to Unsupervised Domain Adaptation [24 Sep 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]
Conference
- 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]
- 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)(PDF Coming Soon)]
- CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency [CVPR2019] [Project]
- 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]
- 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]
- Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes [ICCV2017] [Journal Version]
- No more discrimina- tion: Cross city adaptation of road scene segmenters [ICCV2017]
Journal
- Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes [TIP]
Arxiv
- 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]
Conference
- 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
- Image to Video Domain Adaptation Using Web Supervision [5 Aug 2019]
Conference
- Temporal Attentive Alignment for Large-Scale Video Domain Adaptation [ICCV2019 Oral] [Pytorch]
- Temporal Attentive Alignment for Video Domain Adaptation [CVPRW 2019] [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]
Conference
- Semantic-Transferable Weakly-Supervised Endoscopic Lesions Segmentation [ICCV2019]
- 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]
Conference
- Domain-Adaptive Single-View 3D Reconstruction [ICCV2019]
Arxiv
- DANE: Domain Adaptive Network Embedding [arXiv 3 Jun 2019]
- Active Adversarial Domain Adaptation [arXiv 16 Apr 2019]
Conference
- 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]
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)]
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]
- Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation [arXiv 26 Jun] [Project]