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Existing text-to-video methods struggle to transfer motion smoothly from a reference object to a target object with significant differences in appearance or structure between them. To address this challenge, we introduce MotionShot, a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Yanchen Liu , Yanan Sun , Zhening Xing , Junyao Gao , Kai Chen , Wenjie Pei

Customized generation using diffusion models has made impressive progress in image generation, but remains unsatisfactory in the challenging video generation task, as it requires the controllability of both subjects and motions. To that…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yujie Wei , Shiwei Zhang , Zhiwu Qing , Hangjie Yuan , Zhiheng Liu , Yu Liu , Yingya Zhang , Jingren Zhou , Hongming Shan

Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality images from detailed textual descriptions, they often lack the ability to precisely edit the generated or real images. In this paper, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Chong Mou , Xintao Wang , Jiechong Song , Ying Shan , Jian Zhang

Pre-trained conditional diffusion models have demonstrated remarkable potential in image editing. However, they often face challenges with temporal consistency, particularly in the talking head domain, where continuous changes in facial…

Computer Vision and Pattern Recognition · Computer Science 2025-03-31 Haijie Yang , Zhenyu Zhang , Hao Tang , Jianjun Qian , Jian Yang

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

While recent years have witnessed great progress on using diffusion models for video generation, most of them are simple extensions of image generation frameworks, which fail to explicitly consider one of the key differences between videos…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Jingyun Liang , Yuchen Fan , Kai Zhang , Radu Timofte , Luc Van Gool , Rakesh Ranjan

Large-scale text-to-image models have demonstrated amazing ability to synthesize diverse and high-fidelity images. However, these models are often violated by several limitations. Firstly, they require the user to provide precise and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Yupei Lin , Sen Zhang , Xiaojun Yang , Xiao Wang , Yukai Shi

Controllable generation of 3D human motions becomes an important topic as the world embraces digital transformation. Existing works, though making promising progress with the advent of diffusion models, heavily rely on meticulously captured…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Nhat M. Hoang , Kehong Gong , Chuan Guo , Michael Bi Mi

We present a novel task called online video editing, which is designed to edit \textbf{streaming} frames while maintaining temporal consistency. Unlike existing offline video editing assuming all frames are pre-established and accessible,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Feng Chen , Zhen Yang , Bohan Zhuang , Qi Wu

Controlled video generation has seen drastic improvements in recent years. However, editing actions and dynamic events, or inserting contents that should affect the behaviors of other objects in real-world videos, remains a major challenge.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Vladimir Kulikov , Roni Paiss , Andrey Voynov , Inbar Mosseri , Tali Dekel , Tomer Michaeli

In this work, we present MotionBooth, an innovative framework designed for animating customized subjects with precise control over both object and camera movements. By leveraging a few images of a specific object, we efficiently fine-tune a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Jianzong Wu , Xiangtai Li , Yanhong Zeng , Jiangning Zhang , Qianyu Zhou , Yining Li , Yunhai Tong , Kai Chen

Understanding and modeling lighting effects are fundamental tasks in computer vision and graphics. Classic physically-based rendering (PBR) accurately simulates the light transport, but relies on precise scene representations--explicit 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Ruofan Liang , Zan Gojcic , Huan Ling , Jacob Munkberg , Jon Hasselgren , Zhi-Hao Lin , Jun Gao , Alexander Keller , Nandita Vijaykumar , Sanja Fidler , Zian Wang

Character Animation aims to generating character videos from still images through driving signals. Currently, diffusion models have become the mainstream in visual generation research, owing to their robust generative capabilities. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Li Hu , Xin Gao , Peng Zhang , Ke Sun , Bang Zhang , Liefeng Bo

Recent works have explored text-guided image editing using diffusion models and generated edited images based on text prompts. However, the models struggle to accurately locate the regions to be edited and faithfully perform precise edits.…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Qian Wang , Biao Zhang , Michael Birsak , Peter Wonka

A precise and user-friendly manipulation of image content while preserving image fidelity has always been crucial to the field of image editing. Thanks to the power of generative models, recent point-based image editing methods allow users…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Minxing Luo , Wentao Cheng , Jian Yang

Generating realistic animated videos from static images is an important area of research in computer vision. Methods based on physical simulation and motion prediction have achieved notable advances, but they are often limited to specific…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qiang Wang , Minghua Liu , Junjun Hu , Fan Jiang , Mu Xu

Diffusion-based video editing have reached impressive quality and can transform either the global style, local structure, and attributes of given video inputs, following textual edit prompts. However, such solutions typically incur heavy…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Kumara Kahatapitiya , Adil Karjauv , Davide Abati , Fatih Porikli , Yuki M. Asano , Amirhossein Habibian

Recent advances in generative motion synthesis have enabled the production of realistic human motions from diverse input modalities. However, synthesizing compound actions from texts, which integrate multiple concurrent actions into…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Yue Jiang , Mingyu Yang , Liuyuxin Yang , Yang Xu , Bingxin Yun , Yuhe Zhang

Portrait animation aims to generate photo-realistic videos from a single source image by reenacting the expression and pose from a driving video. While early methods relied on 3D morphable models or feature warping techniques, they often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Mallikarjun B. R. , Fei Yin , Vikram Voleti , Nikita Drobyshev , Maksim Lapin , Aaryaman Vasishta , Varun Jampani

As 3D generation techniques continue to flourish, the demand for generating personalized content is rapidly rising. Users increasingly seek to apply various editing methods to polish generated 3D content, aiming to enhance its color, style,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Weitao Wang , Haoran Xu , Jun Meng , Haoqian Wang