【论文合集】Awesome Segmentation Domain Adaptation
图像分割领域适应相关论文
目录
Semi-supervised DA
Weakly-Supervised DA
Unsupervised DA
Survey
Theory
Explainable
Transfer Learning Paradigms
Object Detection
Semantic Segmentation
Library
Lectures and Tutorials
参考
Semi-supervised DA
Conference
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Multi-level Consistency Learning for Semi-supervised Domain Adaptation [IJCAI 2022]
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AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation [ICLR 2022]
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CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation [NeurIPS]
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Deep Co-Training With Task Decomposition for Semi-Supervised Domain Adaptation [ICCV2021]
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ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation [ICCV2021]
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Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation [CVPR2021]
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Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation [CVPR2021]
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Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation [CVPR2021]
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Improving Semi-Supervised Domain Adaptation Using Effective Target Selection and Semantics [CVPRW2021] [Code]
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Attract, Perturb, and Explore: Learning a Feature Alignment Network for Semi-supervised Domain Adaptation [ECCV2020]
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Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation [ECCV2020]
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Bidirectional Adversarial Training for Semi-Supervised Domain Adaptation [IJCAI2020]
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Semi-supervised Domain Adaptation via Minimax Entropy [ICCV2019] [Pytorch]
Journal
- Context-guided entropy minimization for semi-supervised domain adaptation [Neural Networks] [pytorch]
Arxiv
- MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation [ 24 Jul 2020]
- Opposite Structure Learning for Semi-supervised Domain Adaptation [6 Feb 2020]
- Reducing Domain Gap via Style-Agnostic Networks [25 Oct 2019]
Weakly-Supervised DA
Conference
- Towards Accurate and Robust Domain Adaptation under Noisy Environments [IJCAI2020]
- Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration [CVPR2019]
- Transferable Curriculum for Weakly-Supervised Domain Adaptation [AAAI2019]
Arxiv
- Butterfly: Robust One-step Approach towards Wildly-unsupervised Domain Adaptation [arXiv on 19 May 2019]
Unsupervised DA
Adversarial Methods
Conference
- 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]
- Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation [ECCV2020] [PyTorch]
- 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 [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] [Tensorflow]
- 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
- Incremental Unsupervised Domain-Adversarial Training of Neural Networks [TNNLS 2020]
- Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]
- Adversarial Learning and Interpolation Consistency for Unsupervised Domain Adaptation [IEEE ACCESS]
- TarGAN: Generating target data with class labels for unsupervised domain adaptation [Knowledge-Based Systems]
Arxiv
- Bi-Directional Generation for Unsupervised Domain Adaptation [12 Feb 2020]
- Enlarging Discriminative Power by Adding an Extra Class in Unsupervised Domain Adaptation [19 Feb 2020] [Tensorflow]
- Learning Domain Adaptive Features with Unlabeled Domain Bridges [10 Dec 2019]
- 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]
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
- 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]
Transfer Learning Paradigms
Domain Generalization
Conference
- Sparse Mixture-of-Experts are Domain Generalizable Learners [ICLR2023(Oral)] [Pytorch]
- Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts [NeruIPS2022] [Pytorch]
- Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation [ECCV 2022] [Pytorch]
- Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification [CVPR 2021] [Pytorch]
- Domain Generalization via Inference-time Label-Preserving Target Projections [CVPR2021] [Pytorch]
- Domain Generalization via Entropy Regularization [NeurIPS2020] [Pytorch]
- Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization [NeurIPS2020]
- Learning to Learn with Variational Information Bottleneck for Domain Generalization [ECCV2020]
- Self-Challenging Improves Cross-Domain Generalization [ECCV2020] [Pytorch]
- Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization [ECCV2020] [Pytorch]
- Learning to Balance Specificity and Invariance for In and Out of Domain Generalization [ECCV2020] [Pytorch]
- Learning to Generate Novel Domains for Domain Generalization [ECCV2020]
- Learning to Optimize Domain Specific Normalization for Domain Generalization [ECCV2020]
- Towards Recognizing Unseen Categories in Unseen Domains [ECCV2020] [Pytorch]
- Efficient Domain Generalization via Common-Specific Low-Rank Decomposition [ICML2020] [Pytorch]
- Learning to Learn Single Domain Generalization [CVPR2020] [Pytorch]
- Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition [ICLR2020]
- Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation [ICLR2020]
- Domain Generalization Using a Mixture of Multiple Latent Domains [AAAI2020] [Pytorch]
- Deep Domain-Adversarial Image Generation for Domain Generalisation [Paper] [Pytorch]
- Domain Generalization via Model-Agnostic Learning of Semantic Features [NeurIPS2019] [Tensorflow]
- Episodic Training for Domain Generalization [ICCV2019 Oral] [Pytorch]](GitHub - HAHA-DL/Episodic-DG: This is the repo for the paper "Episodic Training for Domain Generalization" https://arxiv.org/abs/1902.00113)
- 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]
Journal
- Domain Generalization for Regression [IntellManuf2020]
- Correlation-aware Adversarial Domain Adaptation and Generalization [Pattern Recognition(2019)] [code]
Arxiv
- Adversarial Pyramid Network for Video Domain Generalization [8 Dec 2019]
- 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]
Object Detection
Survey
- Unsupervised Domain Adaptation of Object Detectors: A Survey [Arxiv 27 May 2021]
Conference
- Towards Robust Adaptive Object Detection under Noisy Annotations [CVPR2022] [PyTorch]
- H2FA R-CNN: Holistic and Hierarchical Feature Alignment for Cross-Domain Weakly Supervised Object Detection [CVPR2022] [PyTorch] [PaddlePaddle]
- Cross-Domain Adaptive Teacher for Object Detection [CVPR2022] [Project] [PyTorch]
- Task-specific Inconsistency Alignment for Domain Adaptive Object Detection [CVPR2022] [PyTorch]
- SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection [CVPR2022] [PyTorch]
- Single-Domain Generalized Object Detection in Urban Scene via Cyclic-Disentangled Self-Distillation [CVPR2022]
- Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection [CVPR2022]
- Cross Domain Object Detection by Target-Perceived Dual Branch Distillation [CVPR2022]
- Decoupled Adaptation for Cross-Domain Object Detection [ICLR2022] [PyTorch]
- SCAN: Cross Domain Object Detection with Semantic Conditioned Adaptation [AAAI2022] [PyTorch]
- SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection [NeurIPS2021] [Project]
- Multi-Source Domain Adaptation for Object Detection [ICCV2021]
- Knowledge Mining and Transferring for Domain Adaptive Object Detection [ICCV2021]
- Dual Bipartite Graph Learning: A General Approach for Domain Adaptive Object Detection [ICCV2021]
- Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection [ICCV2021]
- Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection [CVPR2021]
- MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection [CVPR2021]
- SRDAN: Scale-aware and Range-aware Domain Adaptation Network for Cross-dataset 3D Object Detection [CVPR2021]
- I3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors [CVPR2021]
- RPN Prototype Alignment for Domain Adaptive Object Detector [CVPR2021]
- ST3D: Self-training for Unsupervised Domain Adaptation on 3D ObjectDetection [CVPR2021]
- Domain-Specific Suppression for Adaptive Object Detection [CVPR2021]
- Unbiased Mean Teacher for Cross-Domain Object Detection [CVPR2021]
- YOLO in the Dark - Domain Adaptation Method for Merging Multiple Models [ECCV2020]
- Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection [ECCV2020]
- One-Shot Unsupervised Cross-Domain Detection [ECCV2020]
- Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector [ECCV2020]
- Adapting Object Detectors with Conditional Domain Normalization [ECCV2020]
- Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions [ECCV2020]
- Domain Adaptive Object Detection via Asymmetric Tri-way Faster-RCNN [ECCV2020]
- Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation [CVPR2020]
- Harmonizing Transferability and Discriminability for Adapting Object Detectors [CVPR2020] [code]
- Exploring Categorical Regularization for Domain Adaptive Object Detection [CVPR2020] [code]
- Cross-domain Detection via Graph-induced Prototype Alignment [CVPR2020 Oral] [code]
- Multi-spectral Salient Object Detection by Adversarial Domain Adaptation [Paper]
- Deep Domain Adaptive Object Detection: a Survey [ICIP2020]
- 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]
- Few-Shot Adaptive Faster R-CNN [CVPR2019]
- Exploring Object Relation in Mean Teacher for Cross-Domain Detection [CVPR2019]
- Adapting Object Detectors via Selective Cross-Domain Alignment [CVPR2019] [Pytorch]
- 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] [Pytorch]
- 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
- Cross-domain object detection using unsupervised image translation [ESWA]
- Pixel and feature level based domain adaptation for object detection in autonomous driving [Neurocomputing]
Arxiv
- See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation [17 Nov 2021]
- Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation [3 Feb 2020]
- Prior-based Domain Adaptive Object Detection for Adverse Weather Conditions [29 Nov 2019]
- Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning [17 Nov 2019]
- Curriculum Self-Paced Learning for Cross-Domain Object Detection [15 Nov 2019]
- SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses [6 Nov 2019]
Semantic Segmentation
Conference
- Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions [WACV 2023] [Pytorch]
- Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation [NeruIPS 2022] [Pytorch]
- DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation [ECCV 2022] [Pytorch]
- HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation [ECCV 2022] [Pytorch]
- Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation [ECCV 2022] [Pytorch]
- DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation [CVPR 2022] [Pytorch]
- Plugging Self-Supervised Monocular Depth into Unsupervised Domain Adaptation for Semantic Segmentation [WACV 2022]
- Shallow Features Guide Unsupervised Domain Adaptation for Semantic Segmentation at Class Boundaries [WACV 2022]
- Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation [NeurIPS2021]
- Dual Path Learning for Domain Adaptation of Semantic Segmentation [ICCV2021]
- Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation [ICCV2021]
- Multi-Anchor Active Domain Adaptation for Semantic Segmentation [ICCV2021]
- LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation [ICCV2021]
- Self-Mutating Network for Domain Adaptive Segmentation in Aerial Images [ICCV2021]
- Geometric Unsupervised Domain Adaptation for Semantic Segmentation [ICCV2021]
- Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation [ICCV2021]
- BAPA-Net: Boundary Adaptation and Prototype Alignment for Cross-Domain Semantic Segmentation [ICCV2021]
- BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation [ICCV2021]
- Uncertainty-Aware Pseudo Label Refinery for Domain Adaptive Semantic Segmentation [ICCV2021]
- Domain Adaptive Semantic Segmentation With Self-Supervised Depth Estimation [ICCV2021]
- Generalize Then Adapt: Source-Free Domain Adaptive Semantic Segmentation [ICCV2021]
- DARCNN: Domain Adaptive Region-Based Convolutional Neural Network for Unsupervised Instance Segmentation in Biomedical Images [CVPR2021]
- DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation [CVPR2021]
- Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation [CVPR2021]
- Complete & Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds [CVPR2021]
- Cluster, Split, Fuse, and Update: Meta-Learning for Open Compound Domain Adaptive Semantic Segmentation [CVPR2021]
- PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Training [CVPR2021] [Pytorch]
- Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation [CVPR2021] [Pytorch]
- Cross-View Regularization for Domain Adaptive Panoptic Segmentation [CVPR2021]
- Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation [CVPR2021]
- MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation [CVPR2021]
- Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization [CVPR2021]
- Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation [CVPR2021]
- Source-Free Domain Adaptation for Semantic Segmentation [CVPR2021]
- Instance Adaptive Self-Training for Unsupervised Domain Adaptation [ECCV 2020] [Pytorch]
- Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning [ICASSP 2020]
- Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation [NeurlIPS 2020] [Pytorch]
- Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation [NeurIPS2020] [Pytorch]
- Semantically Adaptive Image-to-image Translation for Domain Adaptation of Semantic Segmentation [BMVC2020]
- Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation [ECCV2020]
- Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation [ECCV2020]
- Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation [ECCV2020]
- Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images through Generative Latent Search [ECCV2020]
- Domain Adaptive Semantic Segmentation Using Weak Labels [ECCV2020]
- Content-Consistent Matching for Domain Adaptive Semantic Segmentation [ECCV2020] [PyTorch]
- Cross-Domain Semantic Segmentation via Domain-Invariant Interactive Relation Transfer [CVPR2020]
- Phase Consistent Ecological Domain Adaptation [CVPR2020] [Pytorch]
- FDA: Fourier Domain Adaptation for Semantic Segmentation [CVPR2020] [Pytorch]
- Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting [CVPR2020]
- Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision [CVPR2020 Oral] [Pytorch]
- Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation [CVPR2020]
- Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation [CVPR2020] [Pytorch]
- xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation [CVPR2020] [Demo] [code]
- Unsupervised Scene Adaptation with Memory Regularization in vivo [IJCAI2020] [code]
- Joint Adversarial Learning for Domain Adaptation in Semantic Segmentation [AAAI2020]
- An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation [AAAI2020]
- 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]
- Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation [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)]
- CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency [CVPR2019] [Project] [Pytorch]
- 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] [Pytorch]
- 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] [Pytorch]
- Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes [ICCV2017] [Journal Version] [Keras]
- No more discrimination: Cross city adaptation of road scene segmenters [ICCV2017]
Journal
- Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene Segmentation [TIP2022][Pytorch]
- Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation [IJCV2020][Pytorch]
- Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet [Neurocomputing 2021] [Pytorch]
- Affinity Space Adaptation for Semantic Segmentation Across Domains [TIP2020][Pytorch]
- Semantic-aware short path adversarial training for cross-domain semantic segmentation [Neurocomputing 2019]
- Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes [TIP]
Arxiv
- Class-Conditional Domain Adaptation on Semantic Segmentation [27 Nov 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]
- BoMuDA: Boundless Multi-Source Domain Adaptive Segmentation in Unconstrained Environments [13 Oct 2020][Pytorch]
- SAfE: Self-Attention Based Unsupervised Road Safety Classification in Hazardous Environments [27 Nov 2020][Pytorch]
- Semantics-aware Multi-modal Domain Translation:From LiDAR Point Clouds to Panoramic Color Images [26 Jun 2021] [Pytorch]
Library
- Transfer-Learning-Library
- deep-transfer-learning: a PyTorch library for deep transfer learning
- salad: a Semi-supervised Adaptive Learning Across Domains
- Dassl: a PyTorch toolbox for domain adaptation and semi-supervised learning
Lectures and Tutorials
- A Primer on Domain Adaptation [PDF]
参考
Seg-Uncertainty/awesome-SegDA at master · layumi/Seg-Uncertainty · GitHub
GitHub - zhaoxin94/awesome-domain-adaptation: A collection of AWESOME things about domian adaptation