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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Veröffentlicht in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) S. 4300 - 4309
Hauptverfasser:	Xu, Lian, Ouyang, Wanli, Bennamoun, Mohammed, Boussaid, Farid, Xu, Dan
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.06.2022
Schlagworte:	Computer vision grouping and shape analysis Location awareness Object detection Pattern recognition Segmentation Semantics Shape Transformers
ISSN:	1063-6919
Online-Zugang:	Volltext
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