{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/semi-supervised-semantic-segmentation-with-3","title":"Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision","arxiv_id":"2106.01226","date":"2021-06-02","proceeding":"CVPR 2021 1","authors":["Xiaokang Chen","Yuhui Yuan","Gang Zeng","Jingdong Wang"],"abstract":"In this paper, we study the semi-supervised semantic segmentation problem via exploring both labeled data and extra unlabeled data. We propose a novel consistency regularization approach, called cross pseudo supervision (CPS). 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