Matching Adversarial Networks

no code implementations • CVPR 2018 • Gellért Máttyus, Raquel Urtasun

We argue that the main difficulty of applying CGANs to supervised tasks is that the generator training consists of optimizing a loss function that does not depend directly on the ground truth labels.

Depth Estimation Line Detection +1