14 papers
EditTransfer++: Toward Faithful and Efficient Visual-Prompt-Guided Image Editing
Lan Chen, Qi Mao, Yiren Song +2
Visual-prompt-guided edit transfer aims to learn image transformations directly from example pairs, offering more precise and controllable editing than purely text-driven approache…
Mitty: Diffusion-based Human-to-Robot Video Generation
Yiren Song, Cheng Liu, Weijia Mao +1
Learning directly from human demonstration videos is a key milestone toward scalable and generalizable robot learning. Yet existing methods rely on intermediate representations suc…
IC-Effect: Precise and Efficient Video Effects Editing via In-Context Learning
Yuanhang Li, Yiren Song, Junzhe Bai +4
We propose \textbf{IC-Effect}, an instruction-guided, DiT-based framework for few-shot video VFX editing that synthesizes complex effects (\eg flames, particles and cartoon charact…
H2R-Grounder: A Paired-Data-Free Paradigm for Translating Human Interaction Videos into Physically Grounded Robot Videos
Hai Ci, Xiaokang Liu, Pei Yang +2
Robots that learn manipulation skills from everyday human videos could acquire broad capabilities without tedious robot data collection. We propose a video-to-video translation fra…
OmniPSD: Layered PSD Generation with Diffusion Transformer
Cheng Liu, Yiren Song, Haofan Wang +1
Recent advances in diffusion models have greatly improved image generation and editing, yet generating or reconstructing layered PSD files with transparent alpha channels remains h…
The Consistency Critic: Correcting Inconsistencies in Generated Images via Reference-Guided Attentive Alignment
Ziheng Ouyang, Yiren Song, Yaoli Liu +4
Previous works have explored various customized generation tasks given a reference image, but they still face limitations in generating consistent fine-grained details. In this pap…