└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # awesome-domain-adaptation-object-detection 2 | 3 | A collection of papers about domain adaptation object detection. Welcome to PR the works (papers, repositories) that are missed by the repo. 4 | 5 | ## 2023 6 | + [[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 7 | + [[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) 8 | + [[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 9 | + [[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) 10 | + 11 | 12 | ## 2022 13 | 14 | + [[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) 15 | + [[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) 16 | + [[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) 17 | + [[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) H2FA 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) 18 | + [[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) 19 | + [[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) 20 | + [[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 21 | + [[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 22 | + [[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) 23 | + [[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) 24 | + [[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) 25 | + [[ESWA]](https://www.sciencedirect.com/science/article/abs/pii/S0957417421016328) Cross-domain object detection using unsupervised image translation 26 | + [[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 27 | + [[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 28 | + [[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 29 | + [[ARXIV]](https://arxiv.org/abs/2208.14662) AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection 30 | 31 | ## 2021 32 | 33 | + [[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/) 34 | + [[AAAI]](https://ARXIV.org/pdf/2012.05400.pdf) A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data 35 | + [[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) 36 | + [[ARXIV]](https://ARXIV.org/abs/1911.06849v1) Curriculum Self-Paced Learning for Cross-Domain Object Detection 37 | + [[TPAMI]](https://ieeexplore.ieee.org/document/9362301) Instance-Invariant Domain Adaptive Object Detection via Progressive Disentanglement [[CODE]](https://github.com/AmingWu/IIOD) 38 | + [[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 39 | + [[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 40 | + [[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 41 | + [[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 42 | + [[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 43 | + [[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 44 | + [[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 45 | + [[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 46 | 47 | ## 2020 48 | 49 | + [[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) 50 | + [[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) 51 | + [[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) 52 | + [[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 53 | + [[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) 54 | + [[ECCV]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123690307.pdf) Domain Adaptive Object Detection via Asymmetric Tri-way Faster-RCNN 55 | + [[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) 56 | + [[ECCV]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590749.pdf)Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions 57 | + [[ICIP]](https://ARXIV.org/abs/2002.06797v1) Deep Domain Adaptive Object Detection: a Survey 58 | + [[WACV]](https://ARXIV.org/abs/1910.11319) Progressive Domain Adaptation for Object Detection 59 | + [[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 60 | + [[Berkeley]](https://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-69.html) Adapting Across Domains by Aligning Representations and Images 61 | + [[ARXIV]](https://ARXIV.org/abs/1911.07158v1) Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning 62 | + [[ARXIV]](https://ARXIV.org/abs/1912.00070v1) Prior-based Domain Adaptive Object Detection for Adverse Weather Conditions 63 | + [[ARXIV]](https://ARXIV.org/abs/2002.00575v1) Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation 64 | + [[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) 65 | + [[ARXIV]](https://ARXIV.org/pdf/2012.08689.pdf) Domain Adaptive Object Detection via Feature Separation and Alignment 66 | + [[ARXIV]](https://ARXIV.org/pdf/2009.02862.pdf) Channel-wise Alignment for Adaptive Object Detection 67 | + [[ARXIV]](https://ARXIV.org/pdf/2007.02595.pdf) Learning a Domain Classifier Bank for Unsupervised Adaptive Object Detection 68 | + [[ARXIV]](https://ARXIV.org/pdf/2006.14863.pdf) Domain Contrast for Domain Adaptive Object Detection 69 | + [[ARXIV]](https://ARXIV.org/pdf/2006.00821.pdf) Thermal Object Detection using Domain Adaptation through Style Consistency 70 | + [[ARXIV]](https://ARXIV.org/pdf/2004.02093.pdf) Deeply Aligned Adaptation for Cross-domain Object Detection 71 | + [[ARXIV]](https://ARXIV.org/pdf/2003.12943.pdf) Adaptive Object Detection with Dual Multi-Label Prediction 72 | + [[ARXIV]](https://ARXIV.org/pdf/2003.07071.pdf) Adapting Object Detectors with Conditional Domain Normalization [[CODE]](https://github.com/psu1/CDN) 73 | + [[ARXIV]](https://ARXIV.org/pdf/2003.00707.pdf) Unbiased Mean Teacher for Cross Domain Object Detection 74 | + [[ARXIV]](https://ARXIV.org/ftp/ARXIV/papers/2002/2002.06770.pdf) Unsupervised Image-generation Enhanced Adaptation for Object Detection in Thermal images 75 | + [[ARXIV]](https://ARXIV.org/pdf/1912.00070.pdf) Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions 76 | + [[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/) 77 | 78 | ## 2019 79 | 80 | - [[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) 81 | - [[ICCV]](https://ARXIV.org/abs/1909.00597v1) Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection 82 | - [[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 83 | - [[ICCV]](https://ARXIV.org/abs/1907.10343) Multi-adversarial Faster-RCNN for Unrestricted Object Detection 84 | - [[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 85 | - [[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) 86 | - [[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/) 87 | - [[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 88 | - [[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) 89 | - [[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) 90 | - [[BMVC]](https://ARXIV.org/abs/1911.10033) Domain Adaptation for Object Detection via Style Consistency 91 | - [[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) 92 | 93 | ## 2018 94 | 95 | - [[CVPR]](https://ARXIV.org/abs/1803.11365) Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation 96 | - [[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) 97 | --------------------------------------------------------------------------------