"Augmentation Matters: A Simple-Yet-Effective Approach to Semi-Supervised ..."

Zhen Zhao et al. (2023)

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DOI: 10.1109/CVPR52729.2023.01092

access: closed

type: Conference or Workshop Paper

metadata version: 2025-03-03

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Zhen Zhao, Lihe Yang, Sifan Long, Jimin Pi, Luping Zhou, Jingdong Wang:
Augmentation Matters: A Simple-Yet-Effective Approach to Semi-Supervised Semantic Segmentation. CVPR 2023: 11350-11359

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