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complex-yolov3

PyTorch implementation of Complex-YOLO paper with YoloV3

complex-yolov4-pytorch

The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"

demo-spacy-text-processing

fairmot

A simple baseline for one-shot multi-object tracking

kinematic3d

multiyolov5

joint detection and semantic segmentation, based on ultralytics/yolov5,

nanodet

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

odmd

Object Depth via Motion and Detection Dataset

paddle

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

paddlenlp

NLP Core Library and Model Zoo based on PaddlePaddle 2.0

sdc-p5

Udacity Self-Driving Car Project 5: Vehicle Detection and Tracking

sfa3d

Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)

test

test

test_code

abc

trades

Track to Detect and Segment: An Online Multi-Object Tracker (CVPR 2021)

ttnet-real-time-analysis-system-for-table-tennis-pytorch

Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)

yolov5-dnn-cpp-python

用opencv的dnn模块做yolov5目标检测，包含C++和Python两个版本的程序

yolox-opencv-dnn

使用OpenCV部署YOLOX，支持YOLOX-S、YOLOX-M、YOLOX-L、YOLOX-X、YOLOX-Darknet53五种结构，包含C++和Python两种版本的程序