近日，复旦大学的FVL实验室与南洋理工大学的研究人员联合发表了一篇多模态图像编辑综述论文，论文总结了近年的相关研究，涉及超过300篇文献。该研究团队深入探讨了图像和视频编辑以及多模态学习的最新发展，为解决一般性编辑任务提出了一个统一框架。
这篇综述论文指出，图像编辑已经变得越来越普及和关键，无论是日常生活中的照片美化，还是专业领域中的复杂图像生成与修改。论文的核心是提出了一个具有广泛适用性的框架，将编辑过程表示为不同算法族的组合，极大地简化了图像编辑的复杂性。
该综述涵盖自然语言、图像、用户接口等控制条件，以及物体/属性操作、空间变换、图像修复、风格转换、图像翻译和主体/属性客制化等编辑任务。研究团队通过全面的定性和定量实验，详细阐述了各种组合的特性以及适用场景。
此外，机器之心AIxiv专栏也接收了2000多篇关于全球各大高校与企业的顶级实验室的学术、技术内容报道，有效促进了学术交流与传播。如果您有优秀的工作想要分享，欢迎投稿或联系报道。
这篇综述论文为图像编辑领域的研究提供了新的视角和思路，未来，我们期待看到更多创新性的研究和应用在这个领域涌现。
英语如下：
News Title: Fudan and Nanyang Tech Joint Review: A Unified Framework for Multimodal Image Editing Tasks
Keywords: Multimodal Image Editing Review Paper, Unified Framework for General Editing Tasks, Reports from the AIXiv column of The Machine Intelligence Research Institute
News Content:
Fudan University and Nanyang Technological University Research Team Release a Joint Review on Multimodal Image Editing, Proposing a Unified Framework for General Editing Tasks
Recently, the FVL Lab from Fudan University and researchers from Nanyang Technological University jointly published a review paper on multimodal image editing. The paper summarizes recent research involving over 300 literature. The research team delved into the latest developments in image and video editing, as well as multimodal learning, and proposed a unified framework for addressing general editing tasks.
The review paper points out that image editing has become increasingly popular and crucial, ranging from photo beautification in daily life to complex image generation and modification in professional fields. At the core of the paper is the proposal of a broadly applicable framework that represents the editing process as a combination of different algorithm families, greatly simplifying the complexity of image editing.
The review covers control conditions such as natural language, images, and user interfaces, as well as editing tasks including object/attribute manipulation, spatial transformation, image inpainting, style transfer, image translation, and subject/attribute customization. The research team elaborated on the characteristics and applicable scenarios of various combinations through comprehensive qualitative and quantitative experiments.
In addition, the AIXiv column of The Machine Intelligence Research Institute also accepts reports on academic and technological content from top laboratories in various universities and enterprises worldwide, effectively promoting academic exchange and dissemination. If you have excellent work to share, please feel free to submit or contact us for a report.
This review paper provides new perspectives and ideas for research in the field of image editing. In the future, we look forward to seeing more innovative research and applications emerge in this field.
【来源】https://www.jiqizhixin.com/articles/2024-06-28-14
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