A multi-strategy contrastive learning framework for weakly supervised semantic segmentation

A multi-strategy contrastive learning framework for weakly supervised semantic segmentation

Weakly supervised semantic segmentation (WSSS) has gained significant popularity as it relies only on weak labels such as image level annotations rather than the pixel level annotations required by supervised semantic segmentation (SSS) methods. Despite drastically reduced annotation costs, typical...

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Bibliographic Details
Main Authors: Colin Yuan, Gerald Schaefer, Yu-Kun Lai, Yifan Wang, Xiyao Liu, Lin Guan, Hui Fang
Format: Default Article
Published: 2023
Subjects:
Engineering
Information and computing sciences
Information systems
Artificial Intelligence & Image Processing
Weakly supervised learning
Representation learning
Contrastive learning
Semantic segmentation
Online Access:https://hdl.handle.net/2134/21936989.v1
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https://hdl.handle.net/2134/21936989.v1

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