Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation

10/15/2020

∙

by   Hao Li, et al.

∙

10

∙

share

We propose a general framework for searching surrogate losses for mainstream semantic segmentation metrics. This is in contrast to existing loss functions manually designed for individual metrics. The searched surrogate losses can generalize well to other datasets and networks. Extensive experiments on PASCAL VOC and Cityscapes demonstrate the effectiveness of our approach. Code shall be released.