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231226s2023 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2023.3234702
|2 doi
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|a pubmed24n1184.xml
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|a (DE-627)NLM355234076
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Pang, Youwei
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a CAVER
|b Cross-Modal View-Mixed Transformer for Bi-Modal Salient Object Detection
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| 264 |
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|c 2023
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Revised 05.04.2023
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|a published: Print-Electronic
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|a Citation Status Publisher
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|a Most of the existing bi-modal (RGB-D and RGB-T) salient object detection methods utilize the convolution operation and construct complex interweave fusion structures to achieve cross-modal information integration. The inherent local connectivity of the convolution operation constrains the performance of the convolution-based methods to a ceiling. In this work, we rethink these tasks from the perspective of global information alignment and transformation. Specifically, the proposed cross-modal view-mixed transformer (CAVER) cascades several cross-modal integration units to construct a top-down transformer-based information propagation path. CAVER treats the multi-scale and multi-modal feature integration as a sequence-to-sequence context propagation and update process built on a novel view-mixed attention mechanism. Besides, considering the quadratic complexity w.r.t. the number of input tokens, we design a parameter-free patch-wise token re-embedding strategy to simplify operations. Extensive experimental results on RGB-D and RGB-T SOD datasets demonstrate that such a simple two-stream encoder-decoder framework can surpass recent state-of-the-art methods when it is equipped with the proposed components
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|a Journal Article
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1 |
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|a Zhao, Xiaoqi
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Zhang, Lihe
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Lu, Huchuan
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g PP(2023) vom: 11. Jan.
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
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| 773 |
1 |
8 |
|g volume:PP
|g year:2023
|g day:11
|g month:01
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| 856 |
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|u http://dx.doi.org/10.1109/TIP.2023.3234702
|3 Volltext
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|a AR
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| 952 |
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|d PP
|j 2023
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|c 01
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