mlsanityData to 7 Oct 2026

YOLOv3: An Incremental Improvement

arXiv 1804.02767 ↗First posted 8 Apr 2018cs.CVcited by 2,652

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Cited by 36 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We present some updates to YOLO! We made a bunch of little design changes to make it better. We also trained this new network that's pretty swell. It's a little bigger than last time but more accurate. It's still fast though, don't worry. At 320x320 YOLOv3 runs in 22 ms at 28.2 mAP, as accurate as SSD but three times faster. When we look at the old .5 IOU mAP detection metric YOLOv3 is quite good. It achieves 57.9 mAP@50 in 51 ms on a Titan X, compared to 57.5 mAP@50 in 198 ms by RetinaNet, similar performance but 3.8x faster. As always, all the code is online at https://pjreddie.com/yolo/

Key facts. Cited by 2,652 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Apr 2018.

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Citing papers per year: 2018: 1; 2019: 0; 2020: 1; 2021: 591; 2022: 594; 2023: 538; 2024: 448; 2025: 320; 2026: 159.

2,652 papers.

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  1. 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,536
  2. 2021Ego4D: Around the World in 3,000 Hours of Egocentric Videocited by 1,530
  3. 2022DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detectioncited by 1,306
  4. 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,064
  5. 2022YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorscited by 978
  6. 2021ByteTrack: Multi-Object Tracking by Associating Every Detection Boxcited by 812
  7. 2023DETRs Beat YOLOs on Real-time Object Detectioncited by 526
  8. 2024YOLOv10: Real-Time End-to-End Object Detectioncited by 508
  9. 2024YOLO-World: Real-Time Open-Vocabulary Object Detectioncited by 498
  10. 2022DN-DETR: Accelerate DETR Training by Introducing Query DeNoisingcited by 486
  11. 2022ViTPose: Simple Vision Transformer Baselines for Human Pose Estimationcited by 450
  12. 2021Conditional DETR for Fast Training Convergencecited by 422
38 more
  1. 2024YOLOv9: Learning What You Want to Learn Using Programmable Gradient Informationcited by 422
  2. 2024YOLOv11: An Overview of the Key Architectural Enhancementscited by 414
  3. 2021MOTR: End-to-End Multiple-Object Tracking with Transformercited by 379
  4. 2021LAVT: Language-Aware Vision Transformer for Referring Image Segmentationcited by 347
  5. 2022Making the Most of Text Semantics to Improve Biomedical Vision--Language Processingcited by 336
  6. 2022BoT-SORT: Robust Associations Multi-Pedestrian Trackingcited by 313
  7. 2021Unbiased Teacher for Semi-Supervised Object Detectioncited by 305
  8. 2025YOLOv12: Attention-Centric Real-Time Object Detectorscited by 300
  9. 2022YOLOv6: A Single-Stage Object Detection Framework for Industrial Applicationscited by 273
  10. 2021TransVG: End-to-End Visual Grounding with Transformerscited by 269
  11. 2022CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimationcited by 237
  12. 2021LLVIP: A Visible-infrared Paired Dataset for Low-light Visioncited by 229
  13. 2023BEDLAM: A Synthetic Dataset of Bodies Exhibiting Detailed Lifelike Animated Motioncited by 229
  14. 2023Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancementcited by 228
  15. 2022StrongSORT: Make DeepSORT Great Againcited by 213
  16. 2022AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Timecited by 199
  17. 2022RTMDet: An Empirical Study of Designing Real-Time Object Detectorscited by 192
  18. 2021OTA: Optimal Transport Assignment for Object Detectioncited by 177
  19. 2021RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentationcited by 173
  20. 2021You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detectioncited by 170
  21. 2023RTMPose: Real-Time Multi-Person Pose Estimation based on MMPosecited by 170
  22. 2021(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Networkcited by 164
  23. 2022Compute Trends Across Three Eras of Machine Learningcited by 161
  24. 2022Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learningcited by 159
  25. 2022Recurrent Vision Transformers for Object Detection with Event Camerascited by 158
  26. 2023A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAScited by 149
  27. 2021GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimatorcited by 148
  28. 2023PolyFormer: Referring Image Segmentation as Sequential Polygon Generationcited by 147
  29. 2022SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptationcited by 146
  30. 2021FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagerycited by 143
  31. 2021Referring Transformer: A One-step Approach to Multi-task Visual Groundingcited by 143
  32. 2024BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulationcited by 140
  33. 2021Focal and Global Knowledge Distillation for Detectorscited by 138
  34. 2022SeqTR: A Simple yet Universal Network for Visual Groundingcited by 138
  35. 2021Dense Nested Attention Network for Infrared Small Target Detectioncited by 132
  36. 2021The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by Normalizationcited by 131
  37. 2021Probabilistic two-stage detectioncited by 130
  38. 2021Efficient DETR: Improving End-to-End Object Detector with Dense Priorcited by 128

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