Estimate hand pose from an RGB image
Analyze golf images/videos to detect player and club poses
Synthpose Markerless MoCap VitPose
Detect and annotate poses in images and videos
Track chicken poses in real-time
Analyze your squat form with real-time feedback
Create a video using aligned poses from an image and a dance video
Using our method, given a support image and skeleton we can
Detect... human poses in images
Estimate and visualize 3D body poses from video
Detect and visualize human poses in images and videos
Analyze workout posture in real-time
Detect and visualize poses in videos
SAR (State-of-the-Art Rodney) is an advanced AI model designed to estimate hand pose from an RGB image. It leverages cutting-edge computer vision techniques to accurately detect and interpret hand gestures, making it a powerful tool for applications requiring precise hand tracking.
• High accuracy: SAR delivers precise hand pose estimation from RGB images.
• Real-time compatibility: Optimized for real-time applications with minimal latency.
• Versatile integration: Can be seamlessly integrated into various platforms and systems.
What type of input does SAR require?
SAR requires an RGB image as input to estimate hand pose.
Can SAR be used in real-time applications?
Yes, SAR is optimized for real-time applications with minimal latency.
How accurate is SAR for hand pose estimation?
SAR delivers highly accurate hand pose estimation, making it suitable for precise hand tracking applications.