Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders

Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders

Abstract Although the Transformer architecture has established itself as the industry standard for jobs involving natural language processing, it still has few uses in computer vision. In vision, attention is used in conjunction with convolutional networks or to replace individual convolutional netw...

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Bibliographic Details
Main Authors: Muhammad Sajid, Kaleem Razzaq Malik, Ateeq Ur Rehman, Tauqeer Safdar Malik, Masoud Alajmi, Ali Haider Khan, Amir Haider, Seada Hussen
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
2D
Vision Transformers
3D
Masked Autoencoders
2D Semantics
Online Access:https://doi.org/10.1038/s41598-025-87376-y
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https://doi.org/10.1038/s41598-025-87376-y

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