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basketballvideoanalysis

chore

Official implementation for the paper CHORE, ECCV'22

clrnet

Pytorch implementation of our paper "CLRNet: Cross Layer Refinement Network for Lane Detection" (CVPR2022 Acceptance).

coachai-projects

Official research projects of badminton CoachAI

cvpr2022-papers-with-code

CVPR 2022 论文和开源项目合集

external-attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

fiftyone

The open-source tool for building high-quality datasets and computer vision models

fmo-cpp-demo

Fast Moving Objects Detection (demo version)

github-chinese-top-charts

:cn: GitHub中文排行榜，各语言分设「软件 | 资料」榜单，精准定位中文好项目。各取所需，高效学习。

humanseg_android_mnn

lanedetect_android_ncnn

lanedetect_ios_mnn

lanedetect_ios_ncnn

lanedetect_mnn

lanedetect_mnn_android

lanedetect_ncnn

lite-hrnet

This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.

mlsd_pytorch

Pytorch implementation of "M-LSD: Towards Light-weight and Real-time Line Segment Detection"

mlsd_tf

Official Tensorflow implementation of "M-LSD: Towards Light-weight and Real-time Line Segment Detection" (AAAI 2022 Oral)

mmdetection

OpenMMLab Detection Toolbox and Benchmark

mmpose

OpenMMLab Pose Estimation Toolbox and Benchmark.

mmpose0270

mnn-yolov3

MNN demo of Strongeryolo, including channel pruning, android support...

mnnfacedetect

MNN人脸检测轻量化模型部署，模型参数量203KB，适合大部分移动端设备运行。

nanodet

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

ncnn-android-nailseg

paddledetection

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

paddlesports

peoplesanspeople

Unity's privacy-preserving human-centric synthetic data generator

player-reidentification-challenge

A player reidentification challenge on Basketball images. An opportunity to publish at MMSports @ ACMMM and to win 2x $500.