ultralytics/yolov3

Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

YOLOv10: Real-Time End-to-End Object Detection [NeurIPS 2024]

End-to-End Object Detection with Transformers

RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

OpenMMLab Detection Toolbox and Benchmark

Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information