Popular GitHub Repositories for Human Pose

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

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

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models

OpenMMLab Pose Estimation Toolbox and Benchmark.

Gluon CV Toolkit

Effortless data labeling with AI support from Segment Anything and other awesome models.

Real time interactive streaming digital human

StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models

A research prototype of a human-centered web agent

[ICLR 2025] Agent S: an open agentic framework that uses computers like a human

Robust recipes to align language models with human and AI preferences

Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)

Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans

TTS Towards Human-Sounding Speech

PraisonAI is a production-ready Multi AI Agents framework, designed to create AI Agents to automate and solve problems ranging from simple tasks to complex challenges. It provides a low-code solution to streamline the building and management of multi-agent LLM systems, emphasising simplicity, customisation, and effective human-agent collaboration.