APeiZou's repositories
AI4Animation
Bringing Characters to Life with Computer Brains in Unity
awesome-lane-detection
A paper list of lane detection.
awesome-virtual-try-on
A curated list of awesome research papers, projects, code, dataset, workshops etc. related to virtual try-on.
DeepSORT
support deepsort and bytetrack MOT(Multi-object tracking) using yolov5 with C++
DMHead
Dual model head pose estimation. Fusion of SOTA models. 360° 6D HeadPose detection.
EasyMocap
Make human motion capture easier.
free
翻墙、免费翻墙、免费科学上网、免费节点、免费梯子、免费ss/ssr/v2ray/trojan节点、蓝灯、谷歌商店、翻墙梯子
ICCV2021-Paper-Code-Interpretation
ICCV2021/2019/2017 论文/代码/解读/直播合集,极市团队整理
ICCV2021-Papers-with-Code-Demo
ICCV 2021 paper with code
insightface
State-of-the-art 2D and 3D Face Analysis Project
leetcode-master
《代码随想录》LeetCode 刷题攻略:200道经典题目刷题顺序,共60w字的详细图解,视频难点剖析,50余张思维导图,支持C++,Java,Python,Go,JavaScript等多语言版本,从此算法学习不再迷茫!🔥🔥 来看看,你会发现相见恨晚!🚀
mobilevit-pytorch
Unofficial PyTorch implementation of MobileViT.
opensim-core
SimTK OpenSim C++ libraries and command-line applications, and Java/Python wrapping.
Paddle-Lite
Multi-platform high performance deep learning inference engine (『飞桨』多平台高性能深度学习预测引擎)
PaddleDetection
Object detection and instance segmentation toolkit based on PaddlePaddle.
PaddleVideo
Comprehensive, latest, and deployable video deep learning algorithm, including video recognition, action localization, and temporal action detection tasks. It's a high-performance, light-weight codebase provides practical models for video understanding research and application
Person_reID_baseline_pytorch
Pytorch ReID: A tiny, friendly, strong pytorch implement of person re-identification baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
VINS-Fusion
An optimization-based multi-sensor state estimator
yolov5-face
YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931)
YOLOv5-Lite
🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~
yolov7
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors