116 citations · 174 across the 7 of their papers we have counts for
5 papers · 1 filter
Learning Disentangled Prompts for Compositional Image Synthesis
Kihyuk Sohn, Albert Shaw, Yuan Hao +5
We study domain-adaptive image synthesis, the problem of teaching pretrained image generative models a new style or concept from as few as one image to synthesize novel images, to…
Identity Encoder for Personalized Diffusion
Yu-Chuan Su, Kelvin C. K. Chan, Yandong Li +5
Many applications can benefit from personalized image generation models, including image enhancement, video conferences, just to name a few. Existing works achieved personalization…
Taming Encoder for Zero Fine-tuning Image Customization with Text-to-Image Diffusion Models
Xuhui Jia, Yang Zhao, Kelvin C. K. Chan +6
This paper proposes a method for generating images of customized objects specified by users. The method is based on a general framework that bypasses the lengthy optimization requi…
VQ3D: Learning a 3D-Aware Generative Model on ImageNet
Kyle Sargent, Jing Yu Koh, Han Zhang +5
Recent work has shown the possibility of training generative models of 3D content from 2D image collections on small datasets corresponding to a single object class, such as human…
ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation
Han Zhang, Weichong Yin, Yewei Fang +7
Conventional methods for the image-text generation tasks mainly tackle the naturally bidirectional generation tasks separately, focusing on designing task-specific frameworks to im…