vHeat: Building Vision Models upon Heat Conduction

A fundamental problem in learning robust and expressive visual representations lies in efficiently estimating the spatial relationships of visual semantics throughout the entire image. In this study, we propose vHeat, a novel vision backbone model that simultaneously achieves both high computational efficiency and global receptive field.

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Zhaozhi Wang, Yue Liu, Yunfan Liu, Hongtian Yu, Yaowei Wang, Qixiang Ye, Yunjie Tian (2024). Dataset: vHeat: Building Vision Models upon Heat Conduction. https://doi.org/10.57702/oocy8yn8

DOI retrieved: December 16, 2024

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Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2405.16555
Author Zhaozhi Wang
More Authors
Yue Liu
Yunfan Liu
Hongtian Yu
Yaowei Wang
Qixiang Ye
Yunjie Tian