VinAIResearch/LeMul
Toward Realistic Single-View 3D Object Reconstruction with Unsupervised Learning from Multiple Images (ICCV 2021)
This project helps researchers and developers reconstruct the 3D shape and texture of objects from a single image. By analyzing multiple images of the same object type (like faces or cats), it learns to infer a detailed 3D model, outputting realistic 3D representations. It's ideal for those working in computer vision research, 3D content creation, or visual effects.
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Use this if you need to create realistic 3D models from 2D images, especially for object categories where many example images exist.
Not ideal if you need to reconstruct arbitrary, unique objects without a large dataset of similar items for training, or if you require real-time 3D scanning from a single image without prior learning.
Stars
52
Forks
5
Language
Python
License
BSD-3-Clause
Category
Last pushed
Nov 12, 2024
Commits (30d)
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