mlsanityData to 7 Oct 2026

PP-YOLOE: An evolved version of YOLO

arXiv 2203.16250 ↗First posted 30 Mar 2022cs.CVcited by 75

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Abstract (arXiv)

In this report, we present PP-YOLOE, an industrial state-of-the-art object detector with high performance and friendly deployment. We optimize on the basis of the previous PP-YOLOv2, using anchor-free paradigm, more powerful backbone and neck equipped with CSPRepResStage, ET-head and dynamic label assignment algorithm TAL. We provide s/m/l/x models for different practice scenarios. As a result, PP-YOLOE-l achieves 51.4 mAP on COCO test-dev and 78.1 FPS on Tesla V100, yielding a remarkable improvement of (+1.9 AP, +13.35% speed up) and (+1.3 AP, +24.96% speed up), compared to the previous state-of-the-art industrial models PP-YOLOv2 and YOLOX respectively. Further, PP-YOLOE inference speed achieves 149.2 FPS with TensorRT and FP16-precision. We also conduct extensive experiments to verify the effectiveness of our designs. Source code and pre-trained models are available at https://github.com/PaddlePaddle/PaddleDetection.

Key facts. Cited by 75 papers in the map (data through 7 Oct 2026). Builds on 29 of its 35 references that are in the map. First posted on arXiv 30 Mar 2022.

Builds on

29 of 35 references.

References · 29

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2016Densely Connected Convolutional Networkscited by 6,691
  3. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  4. 2017Squeeze-and-Excitation Networkscited by 4,763
  5. 2018YOLOv3: An Incremental Improvementcited by 2,652
  6. 2016Aggregated Residual Transformations for Deep Neural Networkscited by 2,540
  7. 2020YOLOv4: Optimal Speed and Accuracy of Object Detectioncited by 1,624
  8. 2019FCOS: Fully Convolutional One-Stage Object Detectioncited by 1,573
  9. 2017Deformable Convolutional Networkscited by 1,481
  10. 2017Accurate, Large Minibatch SGD: Training ImageNet in 1 Hourcited by 1,479
  11. 2016YOLO9000: Better, Faster, Strongercited by 1,429
  12. 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,064
17 more
  1. 2019EfficientDet: Scalable and Efficient Object Detectioncited by 1,018
  2. 2019Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selectioncited by 539
  3. 2021RepVGG: Making VGG-style ConvNets Great Againcited by 520
  4. 2018Bag of Tricks for Image Classification with Convolutional Neural Networkscited by 430
  5. 2020Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detectioncited by 408
  6. 2019CSPNet: A New Backbone that can Enhance Learning Capability of CNNcited by 381
  7. 2018DropBlock: A regularization method for convolutional networkscited by 261
  8. 2020VarifocalNet: An IoU-aware Dense Object Detectorcited by 230
  9. 2021TOOD: Task-aligned One-stage Object Detectioncited by 218
  10. 2020Scaled-YOLOv4: Scaling Cross Stage Partial Networkcited by 211
  11. 2019An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detectioncited by 163
  12. 2019Learning Spatial Fusion for Single-Shot Object Detectioncited by 59
  13. 2020PP-YOLO: An Effective and Efficient Implementation of Object Detectorcited by 44
  14. 2021PP-YOLOv2: A Practical Object Detectorcited by 30
  15. 2021PP-PicoDet: A Better Real-Time Object Detector on Mobile Devicescited by 25
  16. 2021RMNet: Equivalently Removing Residual Connection from Networkscited by 5
  17. 2021TreeNet: A lightweight One-Shot Aggregation Convolutional Networkcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 10; 2023: 17; 2024: 25; 2025: 12; 2026: 11.

75 papers.

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  1. 2022YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorscited by 978
  2. 2023DETRs Beat YOLOs on Real-time Object Detectioncited by 526
  3. 2024YOLOv10: Real-Time End-to-End Object Detectioncited by 508
  4. 2024YOLO-World: Real-Time Open-Vocabulary Object Detectioncited by 498
  5. 2022InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutionscited by 479
  6. 2024YOLOv9: Learning What You Want to Learn Using Programmable Gradient Informationcited by 422
  7. 2022YOLOv6: A Single-Stage Object Detection Framework for Industrial Applicationscited by 273
  8. 2022RTMDet: An Empirical Study of Designing Real-Time Object Detectorscited by 192
  9. 2023A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAScited by 149
  10. 2024RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformercited by 88
  11. 2024MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretrainingcited by 66
  12. 2023YOLOv6 v3.0: A Full-Scale Reloadingcited by 58
38 more
  1. 2023Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanismcited by 51
  2. 2023FastPillars: A Deployment-friendly Pillar-based 3D Detectorcited by 39
  3. 2022DAMO-YOLO : A Report on Real-Time Object Detection Designcited by 38
  4. 2024LW-DETR: A Transformer Replacement to YOLO for Real-Time Detectioncited by 36
  5. 2023YOLO-MS: Rethinking Multi-Scale Representation Learning for Real-time Object Detectioncited by 33
  6. 2024RT-DETRv3: Real-time End-to-End Object Detection with Hierarchical Dense Positive Supervisioncited by 31
  7. 2024Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computationcited by 29
  8. 2022Make RepVGG Greater Again: A Quantization-aware Approachcited by 21
  9. 2022YOLOV: Making Still Image Object Detectors Great at Video Object Detectioncited by 18
  10. 2023Scene-Driven Multimodal Knowledge Graph Construction for Embodied AIcited by 17
  11. 2023DynamicDet: A Unified Dynamic Architecture for Object Detectioncited by 15
  12. 2025Object Detection with Multimodal Large Vision-Language Models: An In-depth Reviewcited by 14
  13. 2023RefConv: Re-parameterized Refocusing Convolution for Powerful ConvNetscited by 9
  14. 2023Deep Learning Approaches for Seizure Video Analysis: A Reviewcited by 6
  15. 2024YOLOv1 to YOLOv10: The fastest and most accurate real-time object detection systemscited by 6
  16. 2026YOLO26: An Analysis of NMS-Free End to End Framework for Real-Time Object Detectioncited by 6
  17. 2022PP-YOLOE-R: An Efficient Anchor-Free Rotated Object Detectorcited by 5
  18. 2023FemtoDet: An Object Detection Baseline for Energy Versus Performance Tradeoffscited by 5
  19. 2023EfficientRep:An Efficient Repvgg-style ConvNets with Hardware-aware Neural Network Designcited by 5
  20. 2023Language-aware Multiple Datasets Detection Pretraining for DETRscited by 5
  21. 2023YOLOBench: Benchmarking Efficient Object Detectors on Embedded Systemscited by 5
  22. 2024Practical Video Object Detection via Feature Selection and Aggregationcited by 5
  23. 20243DStyleGLIP: Part-Tailored Text-Guided 3D Neural Stylizationcited by 4
  24. 2024Multi-Branch Auxiliary Fusion YOLO with Re-parameterization Heterogeneous Convolutional for accurate object detectioncited by 4
  25. 2025Measuring the Impact of Rotation Equivariance on Aerial Object Detectioncited by 4
  26. 2024Low-Rank Adaption on Transformer-based Oriented Object Detector for Satellite Onboard Processing of Remote Sensing Imagescited by 3
  27. 2024How Important are Data Augmentations to Close the Domain Gap for Object Detection in Orbit?cited by 3
  28. 2025MHAF-YOLO: Multi-Branch Heterogeneous Auxiliary Fusion YOLO for accurate object detectioncited by 3
  29. 2025A Decade of You Only Look Once (YOLO) for Object Detection: A Reviewcited by 3
  30. 2025YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Frameworkcited by 3
  31. 2022FasterX: Real-Time Object Detection Based on Edge GPUs for UAV Applicationscited by 2
  32. 2023BPJDet: Extended Object Representation for Generic Body-Part Joint Detectioncited by 2
  33. 2024Constellation Dataset: Benchmarking High-Altitude Object Detection for an Urban Intersectioncited by 2
  34. 2023CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformercited by 1
  35. 2024YOLO-Ant: A Lightweight Detector via Depthwise Separable Convolutional and Large Kernel Design for Antenna Interference Source Detectioncited by 1
  36. 2024Towards Reflected Object Detection: A Benchmarkcited by 1
  37. 2024FA-YOLO: Research On Efficient Feature Selection YOLO Improved Algorithm Based On FMDS and AGMF Modulescited by 1
  38. 2024Real-Time AIoT for AAV Antenna Interference Detection via Edge-Cloud Collaborationcited by 1

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