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RepPoints: Point Set Representation for Object Detection

arXiv 1904.11490 ↗First posted 25 Apr 2019cs.CVcited by 264

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Abstract (arXiv)

Modern object detectors rely heavily on rectangular bounding boxes, such as anchors, proposals and the final predictions, to represent objects at various recognition stages. The bounding box is convenient to use but provides only a coarse localization of objects and leads to a correspondingly coarse extraction of object features. In this paper, we present RepPoints (representative points), a new finer representation of objects as a set of sample points useful for both localization and recognition. Given ground truth localization and recognition targets for training, RepPoints learn to automatically arrange themselves in a manner that bounds the spatial extent of an object and indicates semantically significant local areas. They furthermore do not require the use of anchors to sample a space of bounding boxes. We show that an anchor-free object detector based on RepPoints can be as effective as the state-of-the-art anchor-based detection methods, with 46.5 AP and 67.4 AP50 on the COCO test-dev detection benchmark, using ResNet-101 model. Code is available at https://github.com/microsoft/RepPoints.

Key facts. Cited by 264 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Apr 2019.

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Citing papers per year: 2021: 71; 2022: 64; 2023: 56; 2024: 32; 2025: 26; 2026: 15.

264 papers.

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  1. 2022DiffusionDet: Diffusion Model for Object Detectioncited by 354
  2. 2021End-to-End Semi-Supervised Object Detection with Soft Teachercited by 315
  3. 2021Focal Self-attention for Local-Global Interactions in Vision Transformerscited by 286
  4. 2022YOLOv6: A Single-Stage Object Detection Framework for Industrial Applicationscited by 273
  5. 2021PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detectioncited by 232
  6. 2021Oriented R-CNN for Object Detectioncited by 230
  7. 2021Dynamic Head: Unifying Object Detection Heads with Attentionscited by 185
  8. 2021OTA: Optimal Transport Assignment for Object Detectioncited by 177
  9. 2021Focal and Global Knowledge Distillation for Detectorscited by 138
  10. 2021Probabilistic two-stage detectioncited by 130
  11. 2021Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergencecited by 130
  12. 2022Towards Large-Scale Small Object Detection: Survey and Benchmarkscited by 119
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  1. 2022MMRotate: A Rotated Object Detection Benchmark using PyTorchcited by 115
  2. 2022Masked Generative Distillationcited by 107
  3. 2021Oriented RepPoints for Aerial Object Detectioncited by 102
  4. 2021TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarioscited by 83
  5. 2021Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detectioncited by 79
  6. 2022Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detectioncited by 79
  7. 20213D-MAN: 3D Multi-frame Attention Network for Object Detectioncited by 73
  8. 2021QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detectioncited by 70
  9. 2022A Keypoint-based Global Association Network for Lane Detectioncited by 68
  10. 2021Back-tracing Representative Points for Voting-based 3D Object Detection in Point Cloudscited by 67
  11. 2021SiamMOT: Siamese Multi-Object Trackingcited by 62
  12. 2021Fully Convolutional Scene Graph Generationcited by 57
  13. 2023Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Reviewcited by 57
  14. 2022Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmarkcited by 56
  15. 2021Adaptive Class Suppression Loss for Long-Tail Object Detectioncited by 55
  16. 2022AO2-DETR: Arbitrary-Oriented Object Detection Transformercited by 55
  17. 2021RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representationcited by 52
  18. 2021A Normalized Gaussian Wasserstein Distance for Tiny Object Detectioncited by 52
  19. 2022RFLA: Gaussian Receptive Field based Label Assignment for Tiny Object Detectioncited by 51
  20. 2023Knowledge Diffusion for Distillationcited by 51
  21. 2022Cross Domain Object Detection by Target-Perceived Dual Branch Distillationcited by 46
  22. 2022Phase-Shifting Coder: Predicting Accurate Orientation in Oriented Object Detectioncited by 43
  23. 2023Dynamic Coarse-to-Fine Learning for Oriented Tiny Object Detectioncited by 43
  24. 2021Anchor-Free Person Searchcited by 42
  25. 2022PKD: General Distillation Framework for Object Detectors via Pearson Correlation Coefficientcited by 41
  26. 2021Disentangle Your Dense Object Detectorcited by 37
  27. 2022H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detectioncited by 36
  28. 2022MTTrans: Cross-Domain Object Detection with Mean-Teacher Transformercited by 35
  29. 2021SOLO: A Simple Framework for Instance Segmentationcited by 32
  30. 2021Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsingcited by 31
  31. 2021A Dataset And Benchmark Of Underwater Object Detection For Robot Pickingcited by 31
  32. 2022Point-to-Box Network for Accurate Object Detection via Single Point Supervisioncited by 31
  33. 2024STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite Imagerycited by 31
  34. 2023H2RBox-v2: Incorporating Symmetry for Boosting Horizontal Box Supervised Oriented Object Detectioncited by 28
  35. 2023Action Sensitivity Learning for Temporal Action Localizationcited by 28
  36. 2021PolarMask++: Enhanced Polar Representation for Single-Shot Instance Segmentation and Beyondcited by 27
  37. 2021G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitationcited by 27
  38. 2023Small Object Detection via Coarse-to-fine Proposal Generation and Imitation Learningcited by 27

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