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The rapid development of diffusion models (DMs) has significantly advanced image and video applications, making "what you want is what you see" a reality. Among these, video editing has gained substantial attention and seen a swift rise in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Wenhao Sun , Rong-Cheng Tu , Jingyi Liao , Dacheng Tao

Image retouching aims to enhance the visual quality of photos. Considering the different aesthetic preferences of users, the target of retouching is subjective. However, current retouching methods mostly adopt deterministic models, which…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Zheng-Peng Duan , Jiawei zhang , Zheng Lin , Xin Jin , Dongqing Zou , Chunle Guo , Chongyi Li

Recent video inpainting algorithms integrate flow-based pixel propagation with transformer-based generation to leverage optical flow for restoring textures and objects using information from neighboring frames, while completing masked…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Xiaowen Li , Haolan Xue , Peiran Ren , Liefeng Bo

Text-to-image diffusion models have shown great potential for image editing, with techniques such as text-based and object-dragging methods emerging as key approaches. However, each of these methods has inherent limitations: text-based…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Haoran Yu , Yi Shi

Recent advancements in large-scale text-to-image diffusion models have enabled many applications in image editing. However, none of these methods have been able to edit the layout of single existing images. To address this gap, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-06-23 Zhiyuan Zhang , Zhitong Huang , Jing Liao

Generative image editing has recently witnessed extremely fast-paced growth. Some works use high-level conditioning such as text, while others use low-level conditioning. Nevertheless, most of them lack fine-grained control over the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Vidit Goel , Elia Peruzzo , Yifan Jiang , Dejia Xu , Xingqian Xu , Nicu Sebe , Trevor Darrell , Zhangyang Wang , Humphrey Shi

Diffusion models have opened the path to a wide range of text-based image editing frameworks. However, these typically build on the multi-step nature of the diffusion backwards process, and adapting them to distilled, fast-sampling methods…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Gilad Deutch , Rinon Gal , Daniel Garibi , Or Patashnik , Daniel Cohen-Or

Large-scale text-to-video models have shown remarkable abilities, but their direct application in video editing remains challenging due to limited available datasets. Current video editing methods commonly require per-video fine-tuning of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Zhenghao Zhang , Zuozhuo Dai , Long Qin , Weizhi Wang

We present MatAtlas, a method for consistent text-guided 3D model texturing. Following recent progress we leverage a large scale text-to-image generation model (e.g., Stable Diffusion) as a prior to texture a 3D model. We carefully design…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Duygu Ceylan , Valentin Deschaintre , Thibault Groueix , Rosalie Martin , Chun-Hao Huang , Romain Rouffet , Vladimir Kim , Gaëtan Lassagne

Accurate and controllable image editing is a challenging task that has attracted significant attention recently. Notably, DragGAN is an interactive point-based image editing framework that achieves impressive editing results with…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Yujun Shi , Chuhui Xue , Jun Hao Liew , Jiachun Pan , Hanshu Yan , Wenqing Zhang , Vincent Y. F. Tan , Song Bai

DragDiffusion is a diffusion-based method for interactive point-based image editing that enables users to manipulate images by directly dragging selected points. The method claims that accurate spatial control can be achieved by optimizing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Ali Subhan , Ashir Raza

Generative models have enabled intuitive image creation and manipulation using natural language. In particular, diffusion models have recently shown remarkable results for natural image editing. In this work, we propose to apply diffusion…

Large-scale Text-to-Image (T2I) diffusion models have revolutionized image generation over the last few years. Although owning diverse and high-quality generation capabilities, translating these abilities to fine-grained image editing…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Chong Mou , Xintao Wang , Jiechong Song , Ying Shan , Jian Zhang

We present the first text-based image editing approach for object parts based on pre-trained diffusion models. Diffusion-based image editing approaches capitalized on the deep understanding of diffusion models of image semantics to perform…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Aleksandar Cvejic , Abdelrahman Eldesokey , Peter Wonka

Recent advances in diffusion transformers have shown remarkable generalization in visual synthesis, yet most dense perception methods still rely on text-to-image (T2I) generators designed for stochastic generation. We revisit this paradigm…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yiqing Shi , Yiren Song , Mike Zheng Shou

We seek to give users precise control over diffusion-based image generation by modeling complex scenes as sequences of layers, which define the desired spatial arrangement and visual attributes of objects in the scene. Collage Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Vishnu Sarukkai , Linden Li , Arden Ma , Christopher Ré , Kayvon Fatahalian

Text-to-video editing aims to edit the visual appearance of a source video conditional on textual prompts. A major challenge in this task is to ensure that all frames in the edited video are visually consistent. Most recent works apply…

Computer Vision and Pattern Recognition · Computer Science 2024-03-04 Yuren Cong , Mengmeng Xu , Christian Simon , Shoufa Chen , Jiawei Ren , Yanping Xie , Juan-Manuel Perez-Rua , Bodo Rosenhahn , Tao Xiang , Sen He

Recent advances in diffusion models enable many powerful instruments for image editing. One of these instruments is text-driven image manipulations: editing semantic attributes of an image according to the provided text description. %…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Nikita Starodubcev , Dmitry Baranchuk , Valentin Khrulkov , Artem Babenko

Despite remarkable achievements in video synthesis, achieving granular control over complex dynamics, such as nuanced movement among multiple interacting objects, still presents a significant hurdle for dynamic world modeling, compounded by…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Pengxiang Li , Kai Chen , Zhili Liu , Ruiyuan Gao , Lanqing Hong , Guo Zhou , Hua Yao , Dit-Yan Yeung , Huchuan Lu , Xu Jia

While 2D diffusion models have achieved remarkable success in identity-preserving personalization, extending this capability to 3D assets remains a significant challenge due to the complexities of multi-view consistency and spatial control.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jinxin Ai , Matthias Nießner , Ziya Erkoç