DualPM/DualPM_Paper
Training, inference and some benchmark code for DualPM presented at CVPR 2025 - Highlight
This project helps computer vision researchers and 3D graphics professionals reconstruct the true 3D shape and orientation of deformable objects from a single image. It takes an image of an object and outputs a pair of point maps representing the object's geometry in both its observed pose and a standardized, canonical pose. This enables detailed 3D modeling and analysis of objects like human bodies or animals from 2D photos.
Use this if you need to precisely recover the 3D geometry and pose of deformable objects from individual images for applications like animation, medical imaging, or virtual reality.
Not ideal if you are working with rigid objects, require real-time processing without offline feature extraction, or do not have access to CUDA-enabled hardware.
Stars
17
Forks
1
Language
Python
License
BSD-3-Clause
Category
Last pushed
Nov 04, 2025
Commits (30d)
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