Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics

CVPR 2018 Alex KendallYarin GalRoberto Cipolla

Numerous deep learning applications benefit from multi-task learning with multiple regression and classification objectives. In this paper we make the observation that the performance of such systems is strongly dependent on the relative weighting between each task's loss... (read more)

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