CLIP is Also an Efficient Segmenter: A Text-Driven Approach for Weakly Supervised Semantic Segmentation

Weakly supervised semantic segmentation (WSSS) with image-level labels is a challenging task. Mainstream approaches follow a multi-stage framework and suffer from high training costs. In this paper, we explore the potential of Contrastive Language-Image Pre-training models (CLIP) to localize differe...

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Veröffentlicht in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) S. 15305 - 15314
Hauptverfasser:	Lin, Yuqi, Chen, Minghao, Wang, Wenxiao, Wu, Boxi, Li, Ke, Lin, Binbin, Liu, Haifeng, He, Xiaofei
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.01.2023
Schlagworte:	Codes Computer vision Costs grouping and shape analysis Pattern recognition Real-time systems Segmentation Semantic segmentation Training
ISSN:	1063-6919
Online-Zugang:	Volltext
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