Move and Act: Enhanced Object Manipulation and Background Integrity for Image Editing
Current methods commonly utilize three-branch structures of inversion, reconstruction, and editing, to tackle consistent image editing task. However, these methods lack control over the generation position of the edited object and have issues with background preservation. To overcome these limitations, we propose a tuning-free method with only two branches: inversion and editing. This approach allows users to simultaneously edit the object's action and control the generation position of the edited object. Additionally, it achieves improved background preservation. Specifically, we transfer the edited object information to the target area and repair or preserve the background of other areas during the inversion process at a specific time step. In the editing stage, we use the image features in self-attention to query the key and value of the corresponding time step in the inversion to achieve consistent image editing. Impressive image editing results and quantitative evaluation demonstrate the effectiveness of our method.
Authors
- Fei Chao (ORCID: https://orcid.org/0000-0002-6928-2638)
- Mingbao Lin (ORCID: https://orcid.org/0000-0003-1764-1894)
- Pengfei Jiang (ORCID: https://orcid.org/0000-0003-3166-5657)
Institutions
- Xiamen University (CN)
- Skyworks Solutions (United States) (US)
Publication Details
- Journal
- Proceedings of the AAAI Conference on Artificial Intelligence
- Published
- 2025-04-11
- DOI
- https://doi.org/10.1609/aaai.v39i4.32423
- Primary Topic
- Generative Adversarial Networks and Image Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province
- National Science and Technology Major Project
- National Science Fund for Distinguished Young Scholars