15 citations · 30 across the 19 of their papers we have counts for
5 papers · 1 filter
ROICtrl: Boosting Instance Control for Visual Generation
Yuchao Gu, Yipin Zhou, Yunfan Ye +5
Natural language often struggles to accurately associate positional and attribute information with multiple instances, which limits current text-based visual generation models to s…
EvolveDirector: Approaching Advanced Text-to-Image Generation with Large Vision-Language Models
Rui Zhao, Hangjie Yuan, Yujie Wei +8
Recent advancements in generation models have showcased remarkable capabilities in generating fantastic content. However, most of them are trained on proprietary high-quality data,…
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Jinheng Xie, Weijia Mao, Zechen Bai +7
We present a unified transformer, i.e., Show-o, that unifies multimodal understanding and generation. Unlike fully autoregressive models, Show-o unifies autoregressive and (discret…
DragAnything: Motion Control for Anything using Entity Representation
Weijia Wu, Zhuang Li, Yuchao Gu +7
We introduce DragAnything, which utilizes a entity representation to achieve motion control for any object in controllable video generation. Comparison to existing motion control m…
Towards A Better Metric for Text-to-Video Generation
Jay Zhangjie Wu, Guian Fang, Haoning Wu +11
Generative models have demonstrated remarkable capability in synthesizing high-quality text, images, and videos. For video generation, contemporary text-to-video models exhibit imp…