26 citations · 29 across the 4 of their papers we have counts for
4 papers
Putting People in Their Place: Affordance-Aware Human Insertion into Scenes
Sumith Kulal, Tim Brooks, Alex Aiken +5
We study the problem of inferring scene affordances by presenting a method for realistically inserting people into scenes. Given a scene image with a marked region and an image of…
Zero-shot Image-to-Image Translation
Gaurav Parmar, Krishna Kumar Singh, Richard Zhang +3
Large-scale text-to-image generative models have shown their remarkable ability to synthesize diverse and high-quality images. However, it is still challenging to directly apply th…
Modulating Pretrained Diffusion Models for Multimodal Image Synthesis
Cusuh Ham, James Hays, Jingwan Lu +3
We present multimodal conditioning modules (MCM) for enabling conditional image synthesis using pretrained diffusion models. Previous multimodal synthesis works rely on training ne…
Scribbler: Controlling Deep Image Synthesis with Sketch and Color
Patsorn Sangkloy, Jingwan Lu, Chen Fang +2
Recently, there have been several promising methods to generate realistic imagery from deep convolutional networks. These methods sidestep the traditional computer graphics renderi…