Visual attention network

While originally designed for natural language processing tasks, the self-attention mechanism has recently taken various computer vision areas by storm. However, the 2D nature of images brings three challenges for applying self-attention in computer vision: (1) treating images as 1D sequences neglec...

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Bibliographic Details
Published in:	Computational visual media (Beijing) Vol. 9; no. 4; pp. 733 - 752
Main Authors:	Guo, Meng-Hao, Lu, Cheng-Ze, Liu, Zheng-Ning, Cheng, Ming-Ming, Hu, Shi-Min
Format:	Journal Article
Language:	English
Published:	Beijing Tsinghua University Press 01.12.2023 Springer Nature B.V SpringerOpen
Subjects:	Artificial Intelligence Artificial neural networks attention Benchmarks Computer Graphics Computer Science Computer vision ConvNets deep learning Image classification Image Processing and Computer Vision Image resolution Image segmentation Natural language processing Neural networks Object recognition Pose estimation Research Article Semantic segmentation Semantics User Interfaces and Human Computer Interaction vision backbone deep learning ConvNets vision backbone attention
ISSN:	2096-0433, 2096-0662
Online Access:	Get full text
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