7 papers
Personalized Vision via Visual In-Context Learning
Yuxin Jiang, Yuchao Gu, Yiren Song +2
Modern vision models, trained on large-scale annotated datasets, excel at predefined tasks but struggle with personalized vision -- tasks defined at test time by users with customi…
UniVid: Unifying Vision Tasks with Pre-trained Video Generation Models
Lan Chen, Yuchao Gu, Qi Mao
Large language models, trained on extensive corpora, successfully unify diverse linguistic tasks within a single generative framework. Inspired by this, recent works like Large Vis…
FramePrompt: In-context Controllable Animation with Zero Structural Changes
Guian Fang, Yuchao Gu, Mike Zheng Shou
Generating controllable character animation from a reference image and motion guidance remains a challenging task due to the inherent difficulty of injecting appearance and motion…
Tuning-Free Image Editing with Fidelity and Editability via Unified Latent Diffusion Model
Qi Mao, Lan Chen, Yuchao Gu +2
Balancing fidelity and editability is essential in text-based image editing (TIE), where failures commonly lead to over- or under-editing issues. Existing methods typically rely on…
Long-Context Autoregressive Video Modeling with Next-Frame Prediction
Yuchao Gu, Weijia Mao, Mike Zheng Shou
Long-context video modeling is essential for enabling generative models to function as world simulators, as they must maintain temporal coherence over extended time spans. However,…
Edit Transfer: Learning Image Editing via Vision In-Context Relations
Lan Chen, Qi Mao, Yuchao Gu +1
We introduce a new setting, Edit Transfer, where a model learns a transformation from just a single source-target example and applies it to a new query image. While text-based meth…