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
- Semi-supervised DA
- Weakly-Supervised DA
- Zero-shot DA
- One-shot DA
- Few-shot UDA
- Few-shot DA
- Partial DA
- Open Set DA
- Universal DA
- Open Compound DA
- Multi Source DA
- Multi Target DA
- Incremental DA
- Multi Step DA
- Heterogeneous DA
- Target-agnostic DA
- Federated DA
- Continuously Indexed DA
- Source Free DA
- Active DA
- Generalized Domain Adaptation
- Model Selection
- Other Transfer Learning Paradigms
- Applications
- Benchmarks
- Library
- Lectures and Tutorials
- Other Resources
Papers
Survey
Arxiv
- Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey [17 Nov 2022] [project]
- A Survey on Deep Domain Adaptation for LiDAR Perception [7 Jun 2021]
- A Comprehensive Survey on Transfer Learning [7 Nov 2019]
- Transfer Adaptation Learning: A Decade Survey [12 Mar 2019]
- A review of single-source unsupervised domain adaptation [16 Jan 2019]
- An introduction to domain adaptation and transfer learning [31 Dec 2018]
- A Survey of Unsupervised Deep Domain Adaptation [6 Dec 2018]
- Transfer Learning for Cross-Dataset Recognition: A Survey [2017]
- Domain Adaptation for Visual Applications: A Comprehensive Survey [2017]
Journal
- Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving [IEEE Access 2023]
- A Review of Single-Source Deep Unsupervised Visual Domain Adaptation [TNNLS 2020]
- Deep Visual Domain Adaptation: A Survey [Neurocomputing 2018]
- A Survey on Deep Transfer Learning [ICANN2018]
- Visual domain adaptation: A survey of recent advances [2015]
Theory
Arxiv
- A Theory of Label Propagation for Subpopulation Shift [22 Feb 2021]
- A General Upper Bound for Unsupervised Domain Adaptation [3 Oct 2019]
- On Deep Domain Adaptation: Some Theoretical Understandings [arXiv 15 Nov 2018]
Conference
- Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift [NeurIPS 2020]
- Bridging Theory and Algorithm for Domain Adaptation [ICML2019] [Pytorch]
- On Learning Invariant Representation for Domain Adaptation [ICML2019] [code]
- Unsupervised Domain Adaptation Based on Source-guided Discrepancy [AAAI2019]
- Learning Bounds for Domain Adaptation [NIPS2007]
- Analysis of Representations for Domain Adaptation [NIPS2006]
Journal
- On a Regularization of Unsupervised Domain Adaptation in RKHS [ACHA2021]
- Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]
- On generalization in moment-based domain adaptation [AMAI2020]
- A theory of learning from different domains [ML2010]
Explainable
Conference
- Visualizing Adapted Knowledge in Domain Transfer [CVPR2021] [Pytorch]
Unsupervised DA
Adversarial Methods
Conference
- SPA: A Graph Spectral Alignment Perspective for Domain Adaptation [NeurIPS 2023] [Pytorch]
- Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation [CVPR2022] [Pytorch]
- A Closer Look at Smoothness in Domain Adversarial Training [ICML2022] [Pytorch]
- ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptation [NeurIPS2021] [Pytorch]
- Adversarial Unsupervised Domain Adaptation With Conditional and Label Shift: Infer, Align and Iterate [ICCV2021]
- Gradient Distribution Alignment Certificates Better Adversarial Domain Adaptation [ICCV2021]
- Re-energizing Domain Discriminator with Sample Relabeling for Adversarial Domain Adaptation [ICCV2021]
- Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation [CVPR2021] [Pytorch]
- MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation [CVPR2021] [Pytorch]
- Self-adaptive Re-weighted Adversarial Domain Adaptation [IJCAI2020]
- DIRL: Domain-Invariant Reperesentation Learning Approach for Sim-to-Real Transfer [CoRL2020] [Project]
- SSA-DA: Bi-dimensional feature alignment for cross-domain object detection [ECCV Workshop 2020]
- Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation [ECCV2020] [PyTorch]
- MCAR: Adaptive object detection with dual multi-label prediction [ECCV2020]
- Gradually Vanishing Bridge for Adversarial Domain Adaptation [CVPR2020] [Pytorch]
- Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation [ICML2020] [Pytorch]
- Adversarial-Learned Loss for Domain Adaptation [AAAI2020]
- Structure-Aware Feature Fusion for Unsupervised Domain Adaptation [AAAI2020]
- Adversarial Domain Adaptation with Domain Mixup [AAAI2020] [Pytorch]
- Discriminative Adversarial Domain Adaptation [AAAI2020] [Pytorch]
- Bi-Directional Generation for Unsupervised Domain Adaptation [AAAI2020]
- Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning [ICASSP 2020]
- Curriculum based Dropout Discriminator for Domain Adaptation [BMVC2019] [Project]
- Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition [IJCNN2019] [Matlab]
- Transfer Learning with Dynamic Adversarial Adaptation Network [ICDM2019]
- Joint Adversarial Domain Adaptation [ACM MM2019]
- Cycle-consistent Conditional Adversarial Transfer Networks [ACM MM2019] [Pytorch]
- Learning Disentangled Semantic Representation for Domain Adaptation [IJCAI2019] [Tensorflow]
- Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation [ICML2019] [Pytorch]
- Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers [ICML2019] [Pytorch]
- Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation [ICCV2019] [PyTorch]
- Cluster Alignment with a Teacher for Unsupervised Domain Adaptation [ICCV2019] [Tensorflow]
- Unsupervised Domain Adaptation via Regularized Conditional Alignment [ICCV2019]
- Attending to Discriminative Certainty for Domain Adaptation [CVPR2019] [Project]
- GCAN: Graph Convolutional Adversarial Network for Unsupervised Domain Adaptation