

Pose Anything
Overview :
Pose Anything is a graph-based general pose estimation method designed to make keypoint localization applicable to any object category using a single model with minimal support image annotations. The method leverages the geometric relationships between keypoints through a novel graph transformer decoder, improving keypoint localization accuracy. Pose Anything has demonstrated outstanding performance on the MP-100 benchmark, surpassing previous state-of-the-art techniques, achieving significant improvements in 1-shot and 5-shot settings. Compared to previous CAPE methods, its end-to-end training exhibits scalability and efficiency.
Target Users :
Pose Anything can be used in the image processing domain, especially in scenarios requiring pose estimation for unknown objects.
Use Cases
Use Pose Anything for pose estimation of unknown objects
Utilize Pose Anything for pose estimation after image classification
Integrate Pose Anything into image processing applications
Features
Support keypoint localization for any object category
Perform pose estimation using a single model
Reduce associated costs
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