O-DisCo-Edit: Object Distortion Control for Unified Realistic Video Editing

Authors

  • Yuqing Chen Tsinghua University Pengcheng National Laboratory
  • Junjie Wang Tsinghua University
  • Lin Liu Huawei Technologies Ltd.
  • Ruihang Chu Tsinghua University
  • Xiaopeng Zhang Huawei Technologies Ltd.
  • Qi Tian Huawei Technologies Ltd.
  • Yujiu Yang Tsinghua University

DOI:

https://doi.org/10.1609/aaai.v40i4.37310

Abstract

Diffusion models have recently advanced video editing, yet controllable editing remains challenging due to the need for precise manipulation of diverse object properties. Current methods require different control signal for diverse editing tasks, which complicates model design and demands significant training resources. To address this, we propose O-DisCo-Edit, a unified framework that incorporates a novel object distortion control (O-DisCo). This signal, based on random and adaptive noise, flexibly encapsulates a wide range of editing cues within a single representation. Paired with a “copy-form” preservation module for preserving non-edited regions, O-DisCo-Edit enables efficient, high-fidelity editing through an effective training paradigm. Extensive experiments and comprehensive human evaluations consistently demonstrate that O-DisCo-Edit surpasses both specialized and multitask state-of-the-art methods across various video editing tasks.

Published

2026-03-14

How to Cite

Chen, Y., Wang, J., Liu, L., Chu, R., Zhang, X., Tian, Q., & Yang, Y. (2026). O-DisCo-Edit: Object Distortion Control for Unified Realistic Video Editing. Proceedings of the AAAI Conference on Artificial Intelligence, 40(4), 3165-3173. https://doi.org/10.1609/aaai.v40i4.37310

Issue

Section

AAAI Technical Track on Computer Vision I