Repository: wangs311/awesome-domain-adaptation-object-detection Branch: master Commit: 01c1d355f33a Files: 1 Total size: 15.6 KB Directory structure: gitextract_njazbjvs/ └── README.md ================================================ FILE CONTENTS ================================================ ================================================ FILE: README.md ================================================ # awesome-domain-adaptation-object-detection A collection of papers about domain adaptation object detection. Welcome to PR the works (papers, repositories) that are missed by the repo. ## 2023 + [[WACV]](https://openaccess.thecvf.com/content/WACV2023/papers/VS_Towards_Online_Domain_Adaptive_Object_Detection_WACV_2023_paper.pdf) Towards Online Domain Adaptive Object Detection + [[WACV]](https://openaccess.thecvf.com/content/WACV2023/papers/Li_Domain_Adaptive_Object_Detection_for_Autonomous_Driving_Under_Foggy_Weather_WACV_2023_paper.pdf)Domain Adaptive Object Detection for Autonomous Driving Under Foggy Weather[[PyTorch]](https://github.com/jinlong17/DA-Detect) + [[WACV]](https://openaccess.thecvf.com/content/WACV2023/papers/Maurya_Domain_Adaptation_Using_Self-Training_With_Mixup_for_One-Stage_Object_Detection_WACV_2023_paper.pdf)Domain Adaptation Using Self-Training With Mixup for One-Stage Object Detection + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_Object_Detection_With_Self-Supervised_Scene_Adaptation_CVPR_2023_paper.pdf) Object Detection with Self-Supervised Scene Adaptation [[CODE]](https://github.com/cvlab-stonybrook/scenes100) + ## 2022 + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2022/papers/Liu_Towards_Robust_Adaptive_Object_Detection_Under_Noisy_Annotations_CVPR_2022_paper.pdf) Towards Robust Adaptive Object Detection under Noisy Annotations [[PyTorch]](https://github.com/CityU-AIM-Group/NLTE) + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2022/papers/Li_Cross-Domain_Adaptive_Teacher_for_Object_Detection_CVPR_2022_paper.pdf) Cross-Domain Adaptive Teacher for Object Detection [[Project]](https://yujheli.github.io/projects/adaptiveteacher.html) [[PyTorch]](https://github.com/facebookresearch/adaptive_teacher) + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2022/papers/Li_SIGMA_Semantic-Complete_Graph_Matching_for_Domain_Adaptive_Object_Detection_CVPR_2022_paper.pdf) SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection [[PyTorch]](https://github.com/CityU-AIM-Group/SIGMA) + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2022/papers/Xu_H2FA_R-CNN_Holistic_and_Hierarchical_Feature_Alignment_for_Cross-Domain_Weakly_CVPR_2022_paper.pdf) H<sup>2</sup>FA R-CNN: Holistic and Hierarchical Feature Alignment for Cross-Domain Weakly Supervised Object Detection [[PyTorch]](https://github.com/XuYunqiu/H2FA_R-CNN) [[PaddlePaddle]](https://github.com/XuYunqiu/H2FA_R-CNN/tree/ppdet) + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhao_Task-Specific_Inconsistency_Alignment_for_Domain_Adaptive_Object_Detection_CVPR_2022_paper.pdf) Task-specific Inconsistency Alignment for Domain Adaptive Object Detection [[PyTorch]](https://github.com/MCG-NJU/TIA) + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2022/papers/Wu_Single-Domain_Generalized_Object_Detection_in_Urban_Scene_via_Cyclic-Disentangled_Self-Distillation_CVPR_2022_paper.pdf) Single-Domain Generalized Object Detection in Urban Scene via Cyclic-Disentangled Self-Distillation [[CODE]](https://github.com/AmingWu/Single-DGOD) + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2022/papers/Wu_Target-Relevant_Knowledge_Preservation_for_Multi-Source_Domain_Adaptive_Object_Detection_CVPR_2022_paper.pdf) Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2022/papers/He_Cross_Domain_Object_Detection_by_Target-Perceived_Dual_Branch_Distillation_CVPR_2022_paper.pdf) Cross Domain Object Detection by Target-Perceived Dual Branch Distillation + [[ICLR]](https://openreview.net/pdf?id=VNqaB1g9393) Decoupled Adaptation for Cross-Domain Object Detection [[PyTorch]](https://github.com/thuml/Decoupled-Adaptation-for-Cross-Domain-Object-Detection) + [[AAAI]](https://www.aaai.org/AAAI22Papers/AAAI-902.LiW.pdf) SCAN: Cross Domain Object Detection with Semantic Conditioned Adaptation [[PyTorch]](https://github.com/CityU-AIM-Group/SCAN) + [[Image and Vision Computing]](https://www.sciencedirect.com/science/article/abs/pii/S0957417421016328) An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites [[CODE]](https://github.com/fpv-iplab/DA-RetinaNet) + [[ESWA]](https://www.sciencedirect.com/science/article/abs/pii/S0957417421016328) Cross-domain object detection using unsupervised image translation + [[WACV]](https://openaccess.thecvf.com/content/WACV2022/papers/VS_Meta-UDA_Unsupervised_Domain_Adaptive_Thermal_Object_Detection_Using_Meta-Learning_WACV_2022_paper.pdf) Meta-UDA: Unsupervised Domain Adaptive Thermal Object Detection Using Meta-Learning + [[WACV]](https://openaccess.thecvf.com/content/WACV2022/papers/Zhong_PICA_Point-Wise_Instance_and_Centroid_Alignment_Based_Few-Shot_Domain_Adaptive_WACV_2022_paper.pdf) PICA: Point-Wise Instance and Centroid Alignment Based Few-Shot Domain Adaptive Object Detection With Loose Annotations + [[WACV]](https://openaccess.thecvf.com/content/WACV2022/papers/Yu_SC-UDA_Style_and_Content_Gaps_Aware_Unsupervised_Domain_Adaptation_for_WACV_2022_paper.pdf) SC-UDA: Style and Content Gaps Aware Unsupervised Domain Adaptation for Object Detection + [[ARXIV]](https://arxiv.org/abs/2208.14662) AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection ## 2021 + [[NeurIPS]](https://proceedings.neurips.cc/paper/2021/file/c0cccc24dd23ded67404f5e511c342b0-Paper.pdf) SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection [[Project]](http://im.itu.edu.pk/synergizing-domain-adaptation/) + [[AAAI]](https://ARXIV.org/pdf/2012.05400.pdf) A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data + [[AAAI]](http://www4.comp.polyu.edu.hk/~cslzhang/paper/AAAI21-CDG.pdf) Category Dictionary Guided Unsupervised Domain Adaptation for Object Detection [probject](https://www.semanticscholar.org/paper/Category-Dictionary-Guided-Unsupervised-Domain-for-Li-Huang/5e412cedaa116ed4d1965dc4815ca56969be1be7) [CODE](https://github.com/strongwolf/CDG) + [[ARXIV]](https://ARXIV.org/abs/1911.06849v1) Curriculum Self-Paced Learning for Cross-Domain Object Detection + [[TPAMI]](https://ieeexplore.ieee.org/document/9362301) Instance-Invariant Domain Adaptive Object Detection via Progressive Disentanglement [[CODE]](https://github.com/AmingWu/IIOD) + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2021/papers/VS_MeGA-CDA_Memory_Guided_Attention_for_Category-Aware_Unsupervised_Domain_Adaptive_Object_CVPR_2021_paper.pdf) MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2021/html/Zhang_RPN_Prototype_Alignment_for_Domain_Adaptive_Object_Detector_CVPR_2021_paper.html) RPN Prototype Alignment for Domain Adaptive Object Detector + [[CVPR]](https://openaccess.thecvf.com/content/CVPR2021/papers/Hou_Informative_and_Consistent_Correspondence_Mining_for_Cross-Domain_Weakly_Supervised_Object_CVPR_2021_paper.pdf) Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection + [[ICCV]](https://openaccess.thecvf.com/content/ICCV2021/papers/Yao_Multi-Source_Domain_Adaptation_for_Object_Detection_ICCV_2021_paper.pdf) Multi-Source Domain Adaptation for Object Detection + [[ICCV]](https://openaccess.thecvf.com/content/ICCV2021/papers/Tian_Knowledge_Mining_and_Transferring_for_Domain_Adaptive_Object_Detection_ICCV_2021_paper.pdf) Knowledge Mining and Transferring for Domain Adaptive Object Detection + [[ICCV]](https://openaccess.thecvf.com/content/ICCV2021/papers/Rezaeianaran_Seeking_Similarities_Over_Differences_Similarity-Based_Domain_Alignment_for_Adaptive_Object_ICCV_2021_paper.pdf) Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection + [[ICCV]](https://openaccess.thecvf.com/content/ICCV2021/papers/Wu_Vector-Decomposed_Disentanglement_for_Domain-Invariant_Object_Detection_ICCV_2021_paper.pdf) Vector-Decomposed Disentanglement for Domain-Invariant Object Detection + [[ICCV]](https://openaccess.thecvf.com/content/ICCV2021/papers/Chen_Dual_Bipartite_Graph_Learning_A_General_Approach_for_Domain_Adaptive_ICCV_2021_paper.pdf) Dual Bipartite Graph Learning: A General Approach for Domain Adaptive Object Detection ## 2020 + [[CVPR]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Chen_Harmonizing_Transferability_and_Discriminability_for_Adapting_Object_Detectors_CVPR_2020_paper.pdf) Harmonizing Transferability and Discriminability for Adapting Object Detectors[[CODE]](https://github.com/chaoqichen/HTCN) + [[CVPR]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Xu_Exploring_Categorical_Regularization_for_Domain_Adaptive_Object_Detection_CVPR_2020_paper.pdf) Exploring Categorical Regularization for Domain Adaptive Object Detection[[CODE]](https://github.com/Megvii-Nanjing/CR-DA-DET) + [[CVPR]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Xu_Cross-Domain_Detection_via_Graph-Induced_Prototype_Alignment_CVPR_2020_paper.pdf) Cross-domain Detection via Graph-induced Prototype Alignment [[CODE]](https://github.com/ChrisAllenMing/GPA-detection) + [[CVPR]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Zheng_Cross-domain_Object_Detection_through_Coarse-to-Fine_Feature_Adaptation_CVPR_2020_paper.pdf) Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation + [[ECCV]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123580477.pdf) Spatial Attention Pyramid Network for Unsupervised Domain Adaptation [[CODE]](https://isrc.iscas.ac.cn/gitlab/research/domain-adaption) + [[ECCV]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123690307.pdf) Domain Adaptive Object Detection via Asymmetric Tri-way Faster-RCNN + [[ECCV]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123630086.pdf) Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection [[CODE]](https://github.com/GanlongZhao/CST_DA_detection) + [[ECCV]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590749.pdf)Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions + [[ICIP]](https://ARXIV.org/abs/2002.06797v1) Deep Domain Adaptive Object Detection: a Survey + [[WACV]](https://ARXIV.org/abs/1910.11319) Progressive Domain Adaptation for Object Detection + [[WACV]](https://openaccess.thecvf.com/content_WACV_2020/papers/Pan_Multi-Scale_Adversarial_Cross-Domain_Detection_with_Robust_Discriminative_Learning_WACV_2020_paper.pdf) Multi-Scale Adversarial Cross-Domain Detection with Robust Discriminative + [[Berkeley]](https://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-69.html) Adapting Across Domains by Aligning Representations and Images + [[ARXIV]](https://ARXIV.org/abs/1911.07158v1) Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning + [[ARXIV]](https://ARXIV.org/abs/1912.00070v1) Prior-based Domain Adaptive Object Detection for Adverse Weather Conditions + [[ARXIV]](https://ARXIV.org/abs/2002.00575v1) Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation + [[ARXIV]](https://ARXIV.org/pdf/2012.08689.pdf) Unsupervised Domain Adaptation from Synthetic to Real Images for Anchorless Object Detection [[CODE]](https://github.com/scheckmedia/centernet-uda) + [[ARXIV]](https://ARXIV.org/pdf/2012.08689.pdf) Domain Adaptive Object Detection via Feature Separation and Alignment + [[ARXIV]](https://ARXIV.org/pdf/2009.02862.pdf) Channel-wise Alignment for Adaptive Object Detection + [[ARXIV]](https://ARXIV.org/pdf/2007.02595.pdf) Learning a Domain Classifier Bank for Unsupervised Adaptive Object Detection + [[ARXIV]](https://ARXIV.org/pdf/2006.14863.pdf) Domain Contrast for Domain Adaptive Object Detection + [[ARXIV]](https://ARXIV.org/pdf/2006.00821.pdf) Thermal Object Detection using Domain Adaptation through Style Consistency + [[ARXIV]](https://ARXIV.org/pdf/2004.02093.pdf) Deeply Aligned Adaptation for Cross-domain Object Detection + [[ARXIV]](https://ARXIV.org/pdf/2003.12943.pdf) Adaptive Object Detection with Dual Multi-Label Prediction + [[ARXIV]](https://ARXIV.org/pdf/2003.07071.pdf) Adapting Object Detectors with Conditional Domain Normalization [[CODE]](https://github.com/psu1/CDN) + [[ARXIV]](https://ARXIV.org/pdf/2003.00707.pdf) Unbiased Mean Teacher for Cross Domain Object Detection + [[ARXIV]](https://ARXIV.org/ftp/ARXIV/papers/2002/2002.06770.pdf) Unsupervised Image-generation Enhanced Adaptation for Object Detection in Thermal images + [[ARXIV]](https://ARXIV.org/pdf/1912.00070.pdf) Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions + [[ACMMM]](https://dl.acm.org/doi/10.1145/3394171.3413553) Domain-Adaptive Object Detection via Uncertainty-Aware Distribution Alignment [CODE](https://github.com/basiclab/DA-OD-MEAA-PyTorch/) ## 2019 - [[IJCNN]](https://ieeexplore.ieee.org/document/8852008) Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night [[Project]](https://github.com/viniciusarruda/cross-domain-car-detection) - [[ICCV]](https://ARXIV.org/abs/1909.00597v1) Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection - [[ICCV]](http://openaccess.thecvf.com/content_ICCV_2019/papers/Khodabandeh_A_Robust_Learning_Approach_to_Domain_Adaptive_Object_Detection_ICCV_2019_paper.pdf) A Robust Learning Approach to Domain Adaptive Object Detection - [[ICCV]](https://ARXIV.org/abs/1907.10343) Multi-adversarial Faster-RCNN for Unrestricted Object Detection - [[CVPR]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Cai_Exploring_Object_Relation_in_Mean_Teacher_for_Cross-Domain_Detection_CVPR_2019_paper.pdf) Exploring Object Relation in Mean Teacher for Cross-Domain Detection - [[CVPR]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhu_Adapting_Object_Detectors_via_Selective_Cross-Domain_Alignment_CVPR_2019_paper.pdf) Adapting Object Detectors via Selective Cross-Domain Alignment [[CODE]](https://github.com/xinge008/SCDA) - [[CVPR]](http://openaccess.thecvf.com/content_CVPR_2019/papers/RoyChowdhury_Automatic_Adaptation_of_Object_Detectors_to_New_Domains_Using_Self-Training_CVPR_2019_paper.pdf)Automatic adaptation of object detectors to new domains using self-training [[Project]](http://vis-www.cs.umass.edu/unsupVideo/) - [[CVPR]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Wang_Towards_Universal_Object_Detection_by_Domain_Attention_CVPR_2019_paper.pdf)Towards Universal Object Detection by Domain Attention - [[CVPR]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Saito_Strong-Weak_Distribution_Alignment_for_Adaptive_Object_Detection_CVPR_2019_paper.pdf)Strong-Weak Distribution Alignment for Adaptive Object Detection [[CODE]](https://github.com/VisionLearningGroup/DA_Detection) - [[CVPR]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Kim_Diversify_and_Match_A_Domain_Adaptive_Representation_Learning_Paradigm_for_CVPR_2019_paper.pdf)Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection [[CODE]](https://github.com/TKKim93/DivMatch) - [[BMVC]](https://ARXIV.org/abs/1911.10033) Domain Adaptation for Object Detection via Style Consistency - [[ARXIV]](https://ARXIV.org/abs/1911.02559v1) SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses [[CODE]](https://github.com/harsh-99/SCL) ## 2018 - [[CVPR]](https://ARXIV.org/abs/1803.11365) Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation - [[CVPR]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Domain_Adaptive_Faster_CVPR_2018_paper.pdf)Domain Adaptive Faster R-CNN for Object Detection in the Wild [[Caffe2]](https://github.com/krumo/Detectron-DA-Faster-RCNN) [[Caffe]](https://github.com/yuhuayc/da-faster-rcnn)
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