SmooSeg: smoothness prior for unsupervised semantic segmentation

SmooSeg: smoothness prior for unsupervised semantic segmentation

Unsupervised semantic segmentation is a challenging task that segments images into semantic groups without manual annotation. Prior works have primarily focused on leveraging prior knowledge of semantic consistency or priori concepts from self-supervised learning methods, which often overlook the co...

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Bibliographic Details
Main Authors: Lan, Mengcheng, Wang, Xinjiang, Ke, Yiping, Xu, Jiaxing, Feng, Litong, Zhang, Wayne
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2024
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Unsupervised Semantic Segmentation
Smoothness Prior
Online Access:https://hdl.handle.net/10356/173324
https://neurips.cc/

Internet

https://hdl.handle.net/10356/173324
https://neurips.cc/

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