2.3k citations · 6.3k across the 28 of their papers we have counts for
4 papers · 1 filter
Seeing What a GAN Cannot Generate
David Bau, Jun-Yan Zhu, Jonas Wulff +4
Despite the success of Generative Adversarial Networks (GANs), mode collapse remains a serious issue during GAN training. To date, little work has focused on understanding and quan…
Connecting Touch and Vision via Cross-Modal Prediction
Yunzhu Li, Jun-Yan Zhu, Russ Tedrake +1
Humans perceive the world using multi-modal sensory inputs such as vision, audition, and touch. In this work, we investigate the cross-modal connection between vision and touch. Th…
Semantic Image Synthesis with Spatially-Adaptive Normalization
Taesung Park, Ming-Yu Liu, Ting-Chun Wang +1
We propose spatially-adaptive normalization, a simple but effective layer for synthesizing photorealistic images given an input semantic layout. Previous methods directly feed the…
On the Units of GANs (Extended Abstract)
David Bau, Jun-Yan Zhu, Hendrik Strobelt +4
Generative Adversarial Networks (GANs) have achieved impressive results for many real-world applications. As an active research topic, many GAN variants have emerged with improveme…