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
    • Self-Supervised Methods
    • Transformer-based Methods
    • Other Methods
  • 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
    • 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
    • Fine-Grained Domain
    • LiDAR
    • Remote Sensing
    • Others
  • 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