This repo is a collection of AWESOME things about domian adaptation,including papers,code etc.Feel free to star and fork.
- Papers
- Code
- Other Resources
- 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]
- Theoretical Perspective of Deep Domain Adaptation [arXiv 15 Nov 2018]
- A theory of learning from different domains [ML2010]
- Learning Bounds for Domain Adaptation [NIPS2007]
- Analysis of Representations for Domain Adaptation [NIPS2006]
- Progressive Feature Alignment for Unsupervised Domain Adaptation [arXiv 21 Nov 2018]
- Conditional Adversarial Domain Adaptation [NIPS2018]
- Unsupervised Domain Adaptation using Generative Models and Self-ensembling [arXiv 2 Dec 2018]
- Exploiting Local Feature Patterns for Unsupervised Domain Adaptation [AAAI2019]
- 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)]
- Augmented Cyclic Adversarial Learning for Domain Adaptation [arXiv 1 Jul 2018]
- 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]
- Simple Domain Adaptation with Class Prediction Uncertainty Alignment [arXiv 12 Apr 2018]
- Causal Generative Domain Adaptation Networks [arXiv 28 Jun 2018]
- 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]
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation [CVPR2018] [Pytorch(Official)]
- Domain Generalization with Adversarial Feature Learning [CVPR2018]
- 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)]
- Incremental Adversarial Domain Adaptation for Continually Changing Environments [ICRA2018]
- A DIRT-T Approach to Unsupervised Domain Adaptation [ICLR2018 Poster] [Tensorflow(Official)]
- Label Efficient Learning of Transferable Representations acrosss Domains and Tasks [NIPS2017] [Project]
- Addressing Appearance Change in Outdoor Robotics with Adversarial Domain Adaptation [IROS2017]
- 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]
- Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation [AAAI2019]
- Boosting Domain Adaptation by Discovering Latent Domains [CVPR2018]
- 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]
- Deep Domain Confusion: Maximizing for Domain Invariance [Arxiv 2014]
- DeepJDOT: Deep Joint distribution optimal transport for unsupervised domain adaptation [ECCV2018]
- 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]
- Transferable Attention for Domain Adaptation [AAAI2019]
- Unsupervised Domain Adaptation: An Adaptive Feature Norm Approach [arXiv 19 Nov 2018]
- Deep Discriminative Learning for Unsupervised Domain Adaptation [arXiv 17 Nov 2018]
- Co-regularized Alignment for Unsupervised Domain Adaptation [NIPS2018]
- Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation [TIP 2018]
- Unsupervised Domain Adaptation by Mapped Correlation Alignment [IEEE ACCESS]
- Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation [ECCV2018]
- 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 Poster]
- Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation [ICLR2018 Poster]
- Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation [CVPR2018]
- Associative Domain Adaptation [ICCV2017] [TensorFlow]
- Learning Transferrable Representations for Unsupervised Domain Adaptation [NIPS2016]
- Transferable Curriculum for Weakly-Supervised Domain Adaptation [AAAI2019]
- Generalized Zero-Shot Learning with Deep Calibration Network NIPS2018
- Zero-Shot Deep Domain Adaptation [ECCV2018]
- 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]
- 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)]
- 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)]
- Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies [NIPS2018]
- Image-to-image translation for cross-domain disentanglement [NIPS2018]
- Learning Factorized Representations for Open-set Domain Adaptation [arXiv 31 May 2018]
- Open Set Domain Adaptation by Backpropagation [ECCV2018] [Tensorflow] [Pytorch]
- Open Set Domain Adaptation [ICCV2017]
- 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)]
- Moment Matching for Multi-Source Domain Adaptation [arXiv 4 Dec 2018]
- Algorithms and Theory for Multiple-Source Adaptation [NIPS2018]
- Adversarial Multiple Source Domain Adaptation [NIPS2018]
- Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift [CVPR2018]
- Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach [arXiv]
- Distant domain transfer learning [AAAI2017]
- Deep Domain Generalization via Conditional Invariant Adversarial Networks [ECCV2018]
- MetaReg: Towards Domain Generalization using Meta-Regularization [NIPS2018]
Unsupervised Learning via Meta-Learning [arXiv]
- Transfer Metric Learning: Algorithms, Applications and Outlooks [arXiv]
- Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation [CVPR2018]
- Domain Adaptive Faster R-CNN for Object Detection in the Wild [CVPR2018]
- ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation [arXiv 30 Nov 2018]
- Unsupervised domain adaptation for medical imaging segmentation with self-ensembling [NIPS2018]
- Domain transfer through deep activation matching [ECCV2018]
- Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training [ECCV2018]
- Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation [CVPR2018]
- Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes [ICCV2017]
- 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]
- 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]
- Unsupervised domain adaptation for medical imaging segmentation with self-ensembling [arXiv 14 Nov 2018]
- Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer [CVPR2018]
- Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation [arXiv 26 Jun] [Project]