Weakly-Supervised Deep Shape-From-Template

We propose WS-DeepSfT, a novel deep learning-based approach to the Shape-from-Template (SfT) problem, which aims at reconstructing the 3D shape of a deformable object from a single RGB image and a template. WS-DeepSfT addresses the limitations of existing SfT techniques by combining a weakly-supervi...

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Bibliographic Details
Main Authors: Sara Luengo-Sanchez, David Fuentes-Jimenez, Cristina Losada-Gutierrez, Daniel Pizarro, Adrien Bartoli
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/10854467/
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