Multi-class Token Transformer for Weakly Supervised Semantic Segmentation

This paper proposes a new transformer-based framework to learn class-specific object localization maps as pseudo labels for weakly supervised semantic segmentation (WSSS). Inspired by the fact that the attended regions of the one-class token in the standard vision transformer can be leveraged to for...

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Vydané v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) s. 4300 - 4309
Hlavní autori:	Xu, Lian, Ouyang, Wanli, Bennamoun, Mohammed, Boussaid, Farid, Xu, Dan
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2022
Predmet:	Computer vision grouping and shape analysis Location awareness Object detection Pattern recognition Segmentation Semantics Shape Transformers
ISSN:	1063-6919
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