6 citations · 11 across the 4 of their papers we have counts for
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cs.CV2021
Collaging Class-specific GANs for Semantic Image Synthesis
Yuheng Li, Yijun Li, Jingwan Lu +3
We propose a new approach for high resolution semantic image synthesis. It consists of one base image generator and multiple class-specific generators. The base generator generates…
cs.CV2021★ 5 cited
IMAGINE: Image Synthesis by Image-Guided Model Inversion
Pei Wang, Yijun Li, Krishna Kumar Singh +2
We introduce an inversion based method, denoted as IMAge-Guided model INvErsion (IMAGINE), to generate high-quality and diverse images from only a single training sample. We levera…
cs.CV2021
Generating Furry Cars: Disentangling Object Shape & Appearance across Multiple Domains
Utkarsh Ojha, Krishna Kumar Singh, Yong Jae Lee
We consider the novel task of learning disentangled representations of object shape and appearance across multiple domains (e.g., dogs and cars). The goal is to learn a generative…