10 citations · 10 across the 1 of their papers we have counts for
3 papers
cs.CV2020
Inclusive GAN: Improving Data and Minority Coverage in Generative Models
Ning Yu, Ke Li, Peng Zhou +3
Generative Adversarial Networks (GANs) have brought about rapid progress towards generating photorealistic images. Yet the equitable allocation of their modeling capacity among sub…
cs.CV2019★ 10 cited
Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture
Ning Yu, Connelly Barnes, Eli Shechtman +2
This paper addresses the problem of interpolating visual textures. We formulate this problem by requiring (1) by-example controllability and (2) realistic and smooth interpolation…
cs.CV2018
Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints
Ning Yu, Larry Davis, Mario Fritz
Recent advances in Generative Adversarial Networks (GANs) have shown increasing success in generating photorealistic images. But they also raise challenges to visual forensics and…