10 citations · 20 across the 5 of their papers we have counts for
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cs.LG2018
Self-Supervised GAN to Counter Forgetting
Ting Chen, Xiaohua Zhai, Neil Houlsby
GANs involve training two networks in an adversarial game, where each network's task depends on its adversary. Recently, several works have framed GAN training as an online or cont…
cs.LG2018
Self-Supervised GANs via Auxiliary Rotation Loss
Ting Chen, Xiaohua Zhai, Marvin Ritter +2
Conditional GANs are at the forefront of natural image synthesis. The main drawback of such models is the necessity for labeled data. In this work we exploit two popular unsupervis…
cs.LG2018
On Self Modulation for Generative Adversarial Networks
Ting Chen, Mario Lucic, Neil Houlsby +1
Training Generative Adversarial Networks (GANs) is notoriously challenging. We propose and study an architectural modification, self-modulation, which improves GAN performance acro…