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Awesome-YOLO-Object-Detection

Awesome

🔥🔥🔥 YOLO is a great real-time one-stage object detection framework. This repository lists some awesome YOLO series projects.

Contents

Review

YOLO Family

Extensional Frameworks

  • YOLOX : "YOLOX: Exceeding YOLO Series in 2021". (arXiv 2021)

  • YOLOR : "You Only Learn One Representation: Unified Network for Multiple Tasks". (arXiv 2021)

  • YOLOF : "You Only Look One-level Feature". (CVPR 2021)

  • YOLOS : "You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection". (NeurIPS 2021)

  • YOLACT & YOLACT++ : You Only Look At CoefficienTs. (ICCV 2019, IEEE TPAMI 2020)

  • jinfagang/yolov7 : 🔥🔥🔥🔥 YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥

  • Alpha-IoU : "Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression". (NeurIPS 2021)

  • CIoU : Complete-IoU (CIoU) Loss and Cluster-NMS for Object Detection and Instance Segmentation (YOLACT). (AAAI 2020, IEEE TCYB 2021)

  • Holocron : PyTorch implementations of recent Computer Vision tricks (ReXNet, RepVGG, Unet3p, YOLOv4, CIoU loss, AdaBelief, PolyLoss).

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🔥🔥🔥 A collection of some awesome YOLO series projects.

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