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Turn ordinary WiFi into a spatial intelligence / sensing system. Detect people, measure breathing and heart rate, track movement, and monitor rooms — through walls, in the dark, with no cameras or wearables. Just physics.

> Motion2MixamoRig is currently experimental. 0 is the command-line pipeline. 2+ Extension that runs that same pipeline in an external Python environment.

Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models are fast, accurate, and easy to use.

CVAT is a leading data annotation platform for image, video, audio, and 3D datasets. It offers open-source, cloud, and enterprise products, as well as labeling services, with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.

X-AnyLabeling: A lightweight, efficient, and unified cross-platform desktop application for annotating text, image, video, and multimodal data, combining versatile built-in tools with state-of-the-art AI models and flexible multi-format export.

This work presents Depth Anything 3 (DA3), a model that predicts spatially consistent geometry from arbitrary visual inputs, with or without known camera poses.

A free-and-open-source, hardware-and-software-agnostic, minimal-cost, research-grade, motion capture system and platform for decentralized scientific research, education, and training

Turn any video into a Mixamo-rig animation - GVHMR estimator, spec-driven retarget, FK apply in Blender via MCP. Works with any Mixamo character; built to be operated end-to-end by an AI agent.

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

Long-horizon streaming reconstruction is often approached by adding increasingly elaborate mechanisms for retaining and fusing long-range state. ABot-Recon takes a deliberately local route. At each time step, it solves the same bounded prediction problem:

1 is released. Those new models will be merged to this repo after we make sure that everything is good.

This repo contains an implementation of the algorithm described in the paper, A Method for Animating Children's Drawings of the Human Figure.

py, which is the same thing with the expression thresholds calibrated to your face instead of to a number I guessed.

live Real-time hand pose detection in the browser using TensorFlow.js. source

To measure accuracy, download COCO-annotations for Pycocotools to the ./coco/annotations/instancesval2017.json

A curated list of deep learning resources for computer vision

Please follow the huggingface download instructions to download the above models and checkpoints, git lfs is recommended.

> ⚠️ Beta: framefields is under active development. APIs may change between releases and some features may be incomplete or unstable.

An enterprise-grade, edge-compatible AI computer vision system designed to detect accidental falls in real-time under severe visual occlusions (behind furniture, tables, beds, couches) while completely eliminating false positives from daily activities such as sitting down…

Egocentric motion reconstruction estimates how a camera moves and how both hands are positioned, oriented, and moving in the surrounding space.

失败任务也会保留 manifest 和日志，便于定位失败阶段。不要让多个任务共用同一个 --output-dir；批处理优先使用 --run-root 与 --task-id。