Popular GitHub Repositories for Map Estimation

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

State-of-the-art 2D and 3D Face Analysis Project

JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js

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.

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

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

OpenMMLab Pose Estimation Toolbox and Benchmark.

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

A highly extensible Markdown editor. Version control, AI Copilot, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement.

Gluon CV Toolkit

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

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

ECCV2022 - Real-Time Intermediate Flow Estimation for Video Frame Interpolation

Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including OpenAI Agents SDK, CrewAI, Langchain, Autogen, AG2, and CamelAI

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

[ICCV 2019] Monocular depth estimation from a single image

A curated list of papers & resources linked to 3D reconstruction from images.

A curated list of action recognition and related area resources

[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.