Detect and highlight key joints in an image
Detect 3D object poses in images
Small Space to test ViTPose
Evaluate and improve your yoga pose accuracy
A visual scorer of two dance videos
Combine and match poses from two videos
Synthpose Markerless MoCap VitPose
Create a video using aligned poses from an image and a dance video
Analyzez une vidéo de danse et affichez les poses 3D
Detect human poses in videos
Analyze images to detect human poses
Estimate camera poses from two images
Estimate human poses in images
Pose Experiment is an innovative tool designed for pose estimation, focusing on detecting and highlighting key joints in an image. It serves as a platform for experimenting with pose detection, making it ideal for developers, researchers, and enthusiasts exploring human pose tracking. Leveraging advanced AI, it provides accurate and versatile pose analysis, enabling deep insights into human movement and posture.
• Real-time processing: Analyze images instantly with fast pose detection. • Multi-person detection: Identify and track poses of multiple individuals in a single image. • Key joint highlighting: Accurately pinpoint and visualize body joints such as shoulders, elbows, knees, and ankles. • High accuracy: Utilizes state-of-the-art AI models for precise pose estimation. • Customizable outputs: Adjust visualization settings, such as joint connections and confidence levels. • Compatibility: Works with various image formats and supports integration into larger applications.
What is the accuracy of Pose Experiment?
Pose Experiment leverages advanced AI models, ensuring high precision in detecting joints and estimating poses.
Can it process multiple people in one image?
Yes, Pose Experiment supports multi-person detection, tracking all individuals in the image simultaneously.
What formats does it support?
It supports common image formats such as JPG, PNG, and BMP.