Official code for BEVDepth.
Dépôts
Dépôts de Megvii-BaseDetection
(875 stars) (121 forks) (0 issues indexées) (0 good first issues ouvertes)
DenseTeacher: Dense Pseudo-Label for Semi-supervised Object Detection
(131 stars) (12 forks) (1 issue indexée) (1 good first issue ouverte)
Megvii-BaseDetection/LLAPython
Official implementation of our paper "LLA: Loss-aware Label Assignment for Dense Pedestrian Detection" in Pytorch.
(36 stars) (3 forks) (0 issues indexées) (0 good first issues ouvertes)
Megvii-BaseDetection/OTAPython
Official implementation of our CVPR2021 paper "OTA: Optimal Transport Assignment for Object Detection" in Pytorch.
(247 stars) (24 forks) (0 issues indexées) (0 good first issues ouvertes)
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
(8 623 stars) (2 069 forks) (2 issues indexées) (2 good first issues ouvertes)