Popular GitHub Repositories for Human Centered

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

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

? 全网效果最好的移动端【实时对话数字人】。 支持本地部署、多模态交互（语音、文本、表情），响应速度低于 1.5 秒，适用于直播、教学、客服、金融、政务等对隐私与实时性要求极高的场景。开箱即用，开发者友好。

A research prototype of a human-centered web agent

OpenMMLab Pose Estimation Toolbox and Benchmark.

Real time interactive streaming digital human

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

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

TTS Towards Human-Sounding Speech

Robust recipes to align language models with human and AI preferences

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.

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

A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)

Relax! Flux is the ML library that doesn't make you tensor

Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"