GSTO: Gated Scale-Transfer Operation for Multi-Scale Feature Learning in Pixel Labeling

27 May 2020Zhuoying WangYongtao WangZhi TangYangyan LiYing ChenHaibin LingWeisi Lin

Existing CNN-based methods for pixel labeling heavily depend on multi-scale features to meet the requirements of both semantic comprehension and detail preservation. State-of-the-art pixel labeling neural networks widely exploit conventional scale-transfer operations, i.e., up-sampling and down-sampling to learn multi-scale features... (read more)

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