华人占大半壁江山！CVPR 2021 目标检测论文大盘点（65篇论文）

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AI/CV重磅干货，第一时间送达

前言

CVer 正式盘点CVPR 2021上各个方向的工作，本篇是热度依然很高的2D目标检测论文大盘点，之前已分享：

  • 最新！CVPR 2021 视觉Transformer论文大盘点（43篇）

  • 最新！CVPR 2021 OCR领域论文大盘点（22篇）

关于更多CVPR 2021的论文和开源代码，可见下面链接：

https://github.com/amusi/CVPR2021-Papers-with-Code

CVPR 2021 2D目标检测论文（65篇）

Amusi 一共搜集了65篇2D目标检测论文，涉及：通用目标检测、旋转目标检测、Few-shot/自监督/半监督/无监督目标检测等方向。

注1：这应该是目前各平台上最新最全面的CVPR 2021 2D目标检测盘点资料，欢迎点赞收藏和分享

注3：65篇中有超过50+篇论文都来自华人，而且至少50+篇都来自中国地区（高校、企业），其中高校以清华、中科院、国科大等为主，企业以旷视、商汤等为主。

2D目标检测

1. Scaled-YOLOv4: Scaling Cross Stage Partial Network

  • Paper: https://arxiv.org/abs/2011.08036

  • Code: https://github.com/WongKinYiu/ScaledYOLOv4

  • 中文解读: YOLOv4官方改进版来了！55.8% AP！速度最高达1774 FPS，Scaled-YOLOv4正式开源！

4. End-to-End Object Detection with Fully Convolutional Network

  • Paper: https://arxiv.org/abs/2012.03544

  • Code: https://github.com/Megvii-BaseDetection/DeFCN

5. Dynamic Head: Unifying Object Detection Heads with Attentions

  • Paper: https://arxiv.org/abs/2106.08322

  • Code: https://github.com/microsoft/DynamicHead

  • 中文解读: 60.6 AP！打破COCO记录！微软提出DyHead：将注意力与目标检测Heads统一

6. Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection

  • Paper: https://arxiv.org/abs/2011.12885

  • Code: https://github.com/implus/GFocalV2

  • 中文解读：CVPR 2021 | GFLV2：目标检测良心技术，无Cost涨点！

7. UP-DETR: Unsupervised Pre-training for Object Detection with Transformers

  • Paper(Oral): https://arxiv.org/abs/2011.09094

  • Code: https://github.com/dddzg/up-detr

  • 中文解读: CVPR 2021 Oral | Transformer再发力！华南理工和微信提出UP-DETR：无监督预训练检测器

13. Multi-Scale Aligned Distillation for Low-Resolution Detection

  • Paper: https://jiaya.me/papers/ms_align_distill_cvpr21.pdf

  • Code: https://github.com/Jia-Research-Lab/MSAD

14. Adaptive Class Suppression Loss for Long-Tail Object Detection

  • Paper: https://arxiv.org/abs/2104.00885

  • Code: https://github.com/CASIA-IVA-Lab/ACSL

15. VarifocalNet: An IoU-aware Dense Object Detector

  • Paper(Oral): https://arxiv.org/abs/2008.13367

  • Code: https://github.com/hyz-xmaster/VarifocalNet

16. OTA: Optimal Transport Assignment for Object Detection

  • Paper: https://arxiv.org/abs/2103.14259

  • Code: https://github.com/Megvii-BaseDetection/OTA

17. Distilling Object Detectors via Decoupled Features

  • Paper: https://arxiv.org/abs/2103.14475

  • Code: https://github.com/ggjy/DeFeat.pytorch

18. Robust and Accurate Object Detection via Adversarial Learning

  • Paper: https://arxiv.org/abs/2103.13886

  • Code: None

19. OPANAS: One-Shot Path Aggregation Network Architecture Search for Object Detection

  • Paper: https://arxiv.org/abs/2103.04507

  • Code: https://github.com/VDIGPKU/OPANAS

20. Multiple Instance Active Learning for Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/papers/Yuan_Multiple_Instance_Active_Learning_for_Object_Detection_CVPR_2021_paper.pdf

  • Code: https://github.com/yuantn/MI-AOD

21. Towards Open World Object Detection

  • Paper(Oral): https://arxiv.org/abs/2103.02603

  • Code: https://github.com/JosephKJ/OWOD

25. Beyond Bounding-Box: Convex-Hull Feature Adaptation for Oriented and Densely Packed Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Guo_Beyond_Bounding-Box_Convex-Hull_Feature_Adaptation_for_Oriented_and_Densely_Packed_CVPR_2021_paper.html

  • Code: https://github.com/SDL-GuoZonghao/BeyondBoundingBox

Few-Shot目标检测

26. Accurate Few-Shot Object Detection With Support-Query Mutual Guidance and Hybrid Loss

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Zhang_Accurate_Few-Shot_Object_Detection_With_Support-Query_Mutual_Guidance_and_Hybrid_CVPR_2021_paper.html

  • Code: None

27. Adaptive Image Transformer for One-Shot Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Chen_Adaptive_Image_Transformer_for_One-Shot_Object_Detection_CVPR_2021_paper.html

  • Code: None

28. Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection

  • Paper: https://arxiv.org/abs/2103.17115

  • Code: https://github.com/hzhupku/DCNet

29. Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection

  • Paper: https://arxiv.org/abs/2103.01903

  • Code: None

30. FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Sun_FSCE_Few-Shot_Object_Detection_via_Contrastive_Proposal_Encoding_CVPR_2021_paper.html

  • Code:  https://github.com/MegviiDetection/FSCE

31. Hallucination Improves Few-Shot Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Zhang_Hallucination_Improves_Few-Shot_Object_Detection_CVPR_2021_paper.html

  • Code: https://github.com/pppplin/HallucFsDet

32. Few-Shot Object Detection via Classification Refinement and Distractor Retreatment

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Li_Few-Shot_Object_Detection_via_Classification_Refinement_and_Distractor_Retreatment_CVPR_2021_paper.html

  • Code: None

33. Generalized Few-Shot Object Detection Without Forgetting

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Fan_Generalized_Few-Shot_Object_Detection_Without_Forgetting_CVPR_2021_paper.html

  • Code: None

41. Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework

  • Paper: https://arxiv.org/abs/2103.11402

  • Code: None

42. Humble Teachers Teach Better Students for Semi-Supervised Object Detection

  • Homepage: https://yihet.com/humble-teacher

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Tang_Humble_Teachers_Teach_Better_Students_for_Semi-Supervised_Object_Detection_CVPR_2021_paper.html

  • Code: https://github.com/lryta/HumbleTeacher

43. Interpolation-Based Semi-Supervised Learning for Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Jeong_Interpolation-Based_Semi-Supervised_Learning_for_Object_Detection_CVPR_2021_paper.html

  • Code: https://github.com/soo89/ISD-SSD

域自适应目标检测

44. Domain-Specific Suppression for Adaptive Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Wang_Domain-Specific_Suppression_for_Adaptive_Object_Detection_CVPR_2021_paper.html

  • Code: None

45. MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection

  • Paper: https://arxiv.org/abs/2103.04224

  • Code: None

46. Unbiased Mean Teacher for Cross-Domain Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Deng_Unbiased_Mean_Teacher_for_Cross-Domain_Object_Detection_CVPR_2021_paper.html

  • Code: https://github.com/kinredon/umt

47. I^3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors

  • Paper: https://arxiv.org/abs/2103.13757

  • Code: None

自监督目标检测

48. There Is More Than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking With Sound by Distilling Multimodal Knowledge

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Valverde_There_Is_More_Than_Meets_the_Eye_Self-Supervised_Multi-Object_Detection_CVPR_2021_paper.html

  • Code: http://rl.uni-freiburg.de/research/multimodal-distill

49. Instance Localization for Self-supervised Detection Pretraining

  • Paper: https://arxiv.org/abs/2102.08318

  • Code: https://github.com/limbo0000/InstanceLoc

弱监督目标检测

50. Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Hou_Informative_and_Consistent_Correspondence_Mining_for_Cross-Domain_Weakly_Supervised_Object_CVPR_2021_paper.html

  • Code: None

51. DAP: Detection-Aware Pre-training with Weak Supervision

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Zhong_DAP_Detection-Aware_Pre-Training_With_Weak_Supervision_CVPR_2021_paper.html

  • Code: None

其他

52. Open-Vocabulary Object Detection Using Captions

  • Paper(Oral): https://openaccess.thecvf.com/content/CVPR2021/html/Zareian_Open-Vocabulary_Object_Detection_Using_Captions_CVPR_2021_paper.html

  • Code: https://github.com/alirezazareian/ovr-cnn

53. Depth From Camera Motion and Object Detection

  • Paper: https://arxiv.org/abs/2103.01468

  • Code: https://github.com/griffbr/ODMD

  • Dataset: https://github.com/griffbr/ODMD

54. Unsupervised Object Detection With LIDAR Clues

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Tian_Unsupervised_Object_Detection_With_LIDAR_Clues_CVPR_2021_paper.html

  • Code: None

55. GAIA: A Transfer Learning System of Object Detection That Fits Your Needs

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Bu_GAIA_A_Transfer_Learning_System_of_Object_Detection_That_Fits_CVPR_2021_paper.html

  • Code: https://github.com/GAIA-vision/GAIA-det

56. General Instance Distillation for Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Dai_General_Instance_Distillation_for_Object_Detection_CVPR_2021_paper.html

  • Code: None

华人占大半壁江山！CVPR 2021 目标检测论文大盘点（65篇论文）

57. AQD: Towards Accurate Quantized Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Chen_AQD_Towards_Accurate_Quantized_Object_Detection_CVPR_2021_paper.html

  • Code: https://github.com/aim-uofa/model-quantization

58. Scale-Aware Automatic Augmentation for Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Chen_Scale-Aware_Automatic_Augmentation_for_Object_Detection_CVPR_2021_paper.html

  • Code: https://github.com/Jia-Research-Lab/SA-AutoAug

59. Equalization Loss v2: A New Gradient Balance Approach for Long-Tailed Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Tan_Equalization_Loss_v2_A_New_Gradient_Balance_Approach_for_Long-Tailed_CVPR_2021_paper.html

  • Code: https://github.com/tztztztztz/eqlv2

60. Class-Aware Robust Adversarial Training for Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Chen_Class-Aware_Robust_Adversarial_Training_for_Object_Detection_CVPR_2021_paper.html

  • Code: None

61. Improved Handling of Motion Blur in Online Object Detection

  • Homepage: http://visual.cs.ucl.ac.uk/pubs/handlingMotionBlur/

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Sayed_Improved_Handling_of_Motion_Blur_in_Online_Object_Detection_CVPR_2021_paper.html

  • Code: None

62. Multiple Instance Active Learning for Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Yuan_Multiple_Instance_Active_Learning_for_Object_Detection_CVPR_2021_paper.html

  • Code: https://github.com/yuantn/MI-AOD

63. Neural Auto-Exposure for High-Dynamic Range Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Onzon_Neural_Auto-Exposure_for_High-Dynamic_Range_Object_Detection_CVPR_2021_paper.html

  • Code: None

64. Generalizable Pedestrian Detection: The Elephant in the Room

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Hasan_Generalizable_Pedestrian_Detection_The_Elephant_in_the_Room_CVPR_2021_paper.html

  • Code: https://github.com/hasanirtiza/Pedestron

65. Neural Auto-Exposure for High-Dynamic Range Object Detection

  • Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Onzon_Neural_Auto-Exposure_for_High-Dynamic_Range_Object_Detection_CVPR_2021_paper.html

  • Code: None

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