Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation

ICCV 2019 Yu ZengYunzhi ZhugeHuchuan LuLihe Zhang

Existing weakly supervised semantic segmentation (WSSS) methods usually utilize the results of pre-trained saliency detection (SD) models without explicitly modeling the connections between the two tasks, which is not the most efficient configuration. Here we propose a unified multi-task learning framework to jointly solve WSSS and SD using a single network, \ie saliency, and segmentation network (SSNet)... (read more)

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