Object-AVEdit: An Object-level Audio-Visual Editing Model
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Abstract (arXiv)
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 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/ObjectAVEdit-website/.
Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 43 of its 48 references that are in the map. First posted on arXiv 27 Sep 2025.
Builds on
43 of 48 references.
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Citing papers per year: 2025: 7; 2026: 7.
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- 2025Explore How to Inject Beneficial Noise in MLLMscited by 10
- 2025AVI-Edit: Audio-sync Video Instance Editing with Granularity-Aware Mask Refinercited by 9
- 2025Rectified Noise: A Generative Model Using Positive-incentive Noisecited by 7
- 2025Laytrol: Preserving Pretrained Knowledge in Layout Control for Multimodal Diffusion Transformerscited by 6
- 2026InstructAV2AV: Instruction-Guided Audio-Video Joint Editingcited by 5
- 2025Schrodinger Audio-Visual Editor: Object-Level Audiovisual Removalcited by 4
- 2026Audio-Visual Intelligence in Large Foundation Modelscited by 2
- 2025JoVA: Unified Multimodal Learning for Joint Video-Audio Generation and Editingcited by 1
- 2026AVE-Compass: Towards Holistic Evaluation for Audio-Video Editing Abilitiescited by 1
- 2025CoLM: Collaborative Large Models via A Client-Server Paradigmcited by 0
- 2026AVENUE: Audio-Video EditiNg Understanding and Evaluationcited by 0
- 2026TV-AudioRemover: Joint Text-Visual Guided Sound Removal with Multi-Task Hard-Mixture Curriculumcited by 0
- 2026AVIO: Learning to Add and Remove Sounding Objects in Audiovisual Scenes29 Sep 2026
- 2026Joint and Cross-Modal Video-Audio Generation and Editing: A Unified Formulation and Design Taxonomy28 Sep 2026
- 2026TV-AudioRemover: Joint Text-Visual Guided Sound Removal with Multi-Task Hard-Mixture Curriculum22 Sep 2026
- 2026AVENUE: Audio-Video EditiNg Understanding and Evaluation31 Aug 2026
- 2026AVE-Compass: Towards Holistic Evaluation for Audio-Video Editing Abilities17 Jul 2026
- 2026InstructAV2AV: Instruction-Guided Audio-Video Joint Editing18 May 2026
- 2026Audio-Visual Intelligence in Large Foundation Models5 May 2026
- 2025JoVA: Unified Multimodal Learning for Joint Video-Audio Generation and Editing15 Dec 2025
- 2025Schrodinger Audio-Visual Editor: Object-Level Audiovisual Removal14 Dec 2025
- 2025AVI-Edit: Audio-sync Video Instance Editing with Granularity-Aware Mask Refiner11 Dec 2025
- 2025Explore How to Inject Beneficial Noise in MLLMs17 Nov 2025
- 2025Laytrol: Preserving Pretrained Knowledge in Layout Control for Multimodal Diffusion Transformers11 Nov 2025
2 more
- 2025Explore How to Inject Beneficial Noise in MLLMscited by 10
- 2025Explore How to Inject Beneficial Noise in MLLMs17 Nov 2025
- 2025AVI-Edit: Audio-sync Video Instance Editing with Granularity-Aware Mask Refinercited by 9
- 2026InstructAV2AV: Instruction-Guided Audio-Video Joint Editingcited by 5
- 2025Schrodinger Audio-Visual Editor: Object-Level Audiovisual Removalcited by 4
- 2026Audio-Visual Intelligence in Large Foundation Modelscited by 2
- 2025JoVA: Unified Multimodal Learning for Joint Video-Audio Generation and Editingcited by 1
- 2026AVE-Compass: Towards Holistic Evaluation for Audio-Video Editing Abilitiescited by 1
- 2025CoLM: Collaborative Large Models via A Client-Server Paradigmcited by 0
- 2026AVENUE: Audio-Video EditiNg Understanding and Evaluationcited by 0
- 2026TV-AudioRemover: Joint Text-Visual Guided Sound Removal with Multi-Task Hard-Mixture Curriculumcited by 0
- 2026Joint and Cross-Modal Video-Audio Generation and Editing: A Unified Formulation and Design Taxonomycited by 0
- 2026AVIO: Learning to Add and Remove Sounding Objects in Audiovisual Scenescited by 0
- 2026AVIO: Learning to Add and Remove Sounding Objects in Audiovisual Scenes29 Sep 2026
- 2026Joint and Cross-Modal Video-Audio Generation and Editing: A Unified Formulation and Design Taxonomy28 Sep 2026
- 2026TV-AudioRemover: Joint Text-Visual Guided Sound Removal with Multi-Task Hard-Mixture Curriculum22 Sep 2026
- 2026AVENUE: Audio-Video EditiNg Understanding and Evaluation31 Aug 2026
- 2026AVE-Compass: Towards Holistic Evaluation for Audio-Video Editing Abilities17 Jul 2026
- 2026InstructAV2AV: Instruction-Guided Audio-Video Joint Editing18 May 2026
- 2026Audio-Visual Intelligence in Large Foundation Models5 May 2026
- 2025JoVA: Unified Multimodal Learning for Joint Video-Audio Generation and Editing15 Dec 2025
- 2025Schrodinger Audio-Visual Editor: Object-Level Audiovisual Removal14 Dec 2025
- 2025AVI-Edit: Audio-sync Video Instance Editing with Granularity-Aware Mask Refiner11 Dec 2025
- 2025CoLM: Collaborative Large Models via A Client-Server Paradigm10 Nov 2025