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AutoAssign: Differentiable Label Assignment for Dense Object Detection

arXiv 2007.03496 ↗First posted 7 Jul 2020cs.CVcited by 100

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Abstract (arXiv)

Determining positive/negative samples for object detection is known as label assignment. Here we present an anchor-free detector named AutoAssign. It requires little human knowledge and achieves appearance-aware through a fully differentiable weighting mechanism. During training, to both satisfy the prior distribution of data and adapt to category characteristics, we present Center Weighting to adjust the category-specific prior distributions. To adapt to object appearances, Confidence Weighting is proposed to adjust the specific assign strategy of each instance. The two weighting modules are then combined to generate positive and negative weights to adjust each location's confidence. Extensive experiments on the MS COCO show that our method steadily surpasses other best sampling strategies by large margins with various backbones. Moreover, our best model achieves 52.1% AP, outperforming all existing one-stage detectors. Besides, experiments on other datasets, e.g., PASCAL VOC, Objects365, and WiderFace, demonstrate the broad applicability of AutoAssign.

Key facts. Cited by 100 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Jul 2020.

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Citing papers per year: 2021: 21; 2022: 30; 2023: 22; 2024: 12; 2025: 12; 2026: 3.

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  1. 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,071
  2. 2022YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorscited by 982
  3. 2021ByteTrack: Multi-Object Tracking by Associating Every Detection Boxcited by 823
  4. 2024YOLOv9: Learning What You Want to Learn Using Programmable Gradient Informationcited by 425
  5. 2025YOLOv12: Attention-Centric Real-Time Object Detectorscited by 305
  6. 2021OTA: Optimal Transport Assignment for Object Detectioncited by 178
  7. 2021You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detectioncited by 170
  8. 2022DETRs with Hybrid Matchingcited by 150
  9. 2021Probabilistic two-stage detectioncited by 130
  10. 2021Efficient DETR: Improving End-to-End Object Detector with Dense Priorcited by 128
  11. 2022Towards Large-Scale Small Object Detection: Survey and Benchmarkscited by 122
  12. 2021You Only Look One-level Featurecited by 116
38 more
  1. 2022Group DETR: Fast DETR Training with Group-Wise One-to-Many Assignmentcited by 98
  2. 2023Dense Distinct Query for End-to-End Object Detectioncited by 77
  3. 2023Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Reviewcited by 58
  4. 2021Localization Distillation for Dense Object Detectioncited by 55
  5. 2022RFLA: Gaussian Receptive Field based Label Assignment for Tiny Object Detectioncited by 51
  6. 2022Equalized Focal Loss for Dense Long-Tailed Object Detectioncited by 46
  7. 2022Label Matching Semi-Supervised Object Detectioncited by 44
  8. 2022Consistent-Teacher: Towards Reducing Inconsistent Pseudo-targets in Semi-supervised Object Detectioncited by 43
  9. 2022DAMO-YOLO : A Report on Real-Time Object Detection Designcited by 38
  10. 2022Towards Data-Efficient Detection Transformerscited by 34
  11. 2023FSD V2: Improving Fully Sparse 3D Object Detection with Virtual Voxelscited by 34
  12. 2024Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinementcited by 31
  13. 2022Real-time Object Detection for Streaming Perceptioncited by 30
  14. 2023Action Sensitivity Learning for Temporal Action Localizationcited by 28
  15. 2022A Dual Weighting Label Assignment Scheme for Object Detectioncited by 26
  16. 2022RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection Systemscited by 23
  17. 2021A General Gaussian Heatmap Label Assignment for Arbitrary-Oriented Object Detectioncited by 22
  18. 2023Object Detection with Transformers: A Reviewcited by 22
  19. 2022ConQueR: Query Contrast Voxel-DETR for 3D Object Detectioncited by 21
  20. 2021IQDet: Instance-wise Quality Distribution Sampling for Object Detectioncited by 20
  21. 2022Localization Distillation for Object Detectioncited by 19
  22. 2021Improving Object Detection by Label Assignment Distillationcited by 17
  23. 2023Efficient Teacher: Semi-Supervised Object Detection for YOLOv5cited by 17
  24. 2022Active Pointly-Supervised Instance Segmentationcited by 15
  25. 2022Prediction-Guided Distillation for Dense Object Detectioncited by 14
  26. 2023Rigidity-Aware Detection for 6D Object Pose Estimationcited by 13
  27. 2021Mutual Supervision for Dense Object Detectioncited by 10
  28. 2022Domain generalization in deep learning-based mass detection in mammography: A large-scale multi-center studycited by 10
  29. 2022Boosting R-CNN: Reweighting R-CNN Samples by RPN's Error for Underwater Object Detectioncited by 10
  30. 2024Background Semantics Matter: Cross-Task Feature Exchange Network for Clustered Infrared Small Target Detectioncited by 9
  31. 2025FSHNet: Fully Sparse Hybrid Network for 3D Object Detectioncited by 9
  32. 2022Logit Normalization for Long-tail Object Detectioncited by 8
  33. 2023One-to-Few Label Assignment for End-to-End Dense Detectioncited by 8
  34. 2023StageInteractor: Query-based Object Detector with Cross-stage Interactioncited by 8
  35. 2024DenoDet: Attention as Deformable Multi-Subspace Feature Denoising for Target Detection in SAR Imagescited by 8
  36. 2021LLA: Loss-aware Label Assignment for Dense Pedestrian Detectioncited by 7
  37. 2022Dynamic Label Assignment for Object Detection by Combining Predicted IoUs and Anchor IoUscited by 6
  38. 2021TE-YOLOF: Tiny and efficient YOLOF for blood cell detectioncited by 5

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