Awsome Domain-Adaptation
2018-08-06 19:27:54
This blog is copied from: https://github.com/zhaoxin94/awsome-domain-adaptation
This repo is a collection of AWESOME things about domian adaptation,including papers,code etc.Feel free to star and fork.
Contents
- Papers
- Overview
- Theory
- Unsupervised DA
- Adversarial Methods
- Network Methods
- Optimal Transport
- Incremental Methods
- Other Methods
- Zero-shot DA
- Few-shot DA
- Image-to-Image Translation
- Open Set DA
- Partial DA
- Multi-source DA
- General Transfer Learning
- Applications
- Object Detection
- Semantic Segmentation
- Person Re-Identification
- Others
- Benchmarks
Papers
Overview
- Deep Visual Domain Adaptation: A Survey [arXiv 2018]
- Domain Adaptation for Visual Applications: A Comprehensive Survey [arXiv 2017]
Theory
- Analysis of Representations for Domain Adaptation [NIPS2006]
- A theory of learning from different domains [ML2010]
- Learning Bounds for Domain Adaptation [NIPS2007]
Unsupervised DA
Adversarial Methods
- 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]
- Conditional Adversarial Domain Adaptation [arXiv 10 Feb 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]
Network Methods
- 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]
Optimal Transport
- 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 Methods
- Incremental Adversarial Domain Adaptation for Continually Changing Environments [ICRA2018]
- Continuous Manifold based Adaptation for Evolving Visual Domains [CVPR2014]
Other Methods
- Unsupervised Domain Adaptation with Distribution Matching Machines [AAAI2018]
- 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]
Zero-shot DA
- Zero-Shot Deep Domain Adaptation [ECCV2018]
Few-shot DA
Image-to-Image Translation
- JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets [ICML2018] [TensorFlow(Official)]
- Multimodal Unsupervised Image-to-Image Translation [arXiv] [Pytorch(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] [Poytorch(Official)]
Open Set DA
- Learning Factorized Representations for Open-set Domain Adaptation [arXiv 31 May 2018]
- Open Set Domain Adaptation by Backpropagation [ECCV2018]
- Open Set Domain Adaptation [ICCV2017]
Partial DA
- Partial Adversarial Domain Adaptation [ECCV2018(not released)] [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)]
Multi source DA
- Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift [CVPR2018]
Applications
Object Detection
- Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation [CVPR2018]
- Domain Adaptive Faster R-CNN for Object Detection in the Wild [CVPR2018]
Semantic Segmentation
- Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation [CVPR2018]
- Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes [ICCV2017]
Person Re-identification
- 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]
Others
- Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer [CVPR2018]
Benchmarks
- Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation [arXiv 26 Jun] [Project]