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Object-AVEdit: An Object-level Audio-Visual Editing Model

Published: September 27, 2025 | arXiv ID: 2510.00050v1

By: Youquan Fu , Ruiyang Si , Hongfa Wang and more

BigTech Affiliations: Huawei Tencent

Potential Business Impact:

Changes sounds and pictures of objects in videos.

Business Areas:
Video Editing Content and Publishing, Media and Entertainment, Video

There is a high demand for audio-visual editing in video post-production and the film making field. While numerous models have explored audio and video editing, they struggle with object-level audio-visual operations. Specifically, object-level audio-visual editing requires the ability to perform object addition, replacement, and removal across both audio and visual modalities, while preserving the structural information of the source instances during the editing process. In this paper, we present \textbf{Object-AVEdit}, achieving the object-level audio-visual editing based on the inversion-regeneration paradigm. To achieve the object-level controllability during editing, we develop a word-to-sounding-object well-aligned audio generation model, bridging the gap in object-controllability between audio and current video generation models. Meanwhile, to achieve the better structural information preservation and object-level editing effect, we propose an inversion-regeneration holistically-optimized editing algorithm, ensuring both information retention during the inversion and better regeneration effect. Extensive experiments demonstrate that our editing model achieved advanced results in both audio-video object-level editing tasks with fine audio-visual semantic alignment. In addition, our developed audio generation model also achieved advanced performance. More results on our project page: https://gewu-lab.github.io/Object_AVEdit-website/.

Country of Origin
🇨🇳 China

Page Count
16 pages

Category
Computer Science:
Multimedia