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Text-based talking-head video editing aims to efficiently insert, delete, and substitute segments of talking videos through a user-friendly text editing approach. It is challenging because of \textbf{1)} generalizable talking-face…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Bo Han , Heqing Zou , Haoyang Li , Guangcong Wang , Chng Eng Siong

Existing diffusion-based methods have achieved impressive results in human motion editing. However, these methods often exhibit significant ghosting and body distortion in unseen in-the-wild cases. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Yi Zuo , Lingling Li , Licheng Jiao , Fang Liu , Xu Liu , Wenping Ma , Shuyuan Yang , Yuwei Guo

Facial video editing has become increasingly important for content creators, enabling the manipulation of facial expressions and attributes. However, existing models encounter challenges such as poor editing quality, high computational…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Tharun Anand , Aryan Garg , Kaushik Mitra

Despite significant advances in modeling image priors via diffusion models, 3D-aware image editing remains challenging, in part because the object is only specified via a single image. To tackle this challenge, we propose 3D-Fixup, a new…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Yen-Chi Cheng , Krishna Kumar Singh , Jae Shin Yoon , Alex Schwing , Liangyan Gui , Matheus Gadelha , Paul Guerrero , Nanxuan Zhao

The development of diffusion models has significantly advanced the research on image stylization, particularly in the area of stylizing a content image based on a given style image, which has attracted many scholars. The main challenge in…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Zhaoli Deng , Kaibin Zhou , Fanyi Wang , Zhenpeng Mi

Diffusion models have achieved significant success in image and video generation. This motivates a growing interest in video editing tasks, where videos are edited according to provided text descriptions. However, most existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Zhen Xing , Qi Dai , Zihao Zhang , Hui Zhang , Han Hu , Zuxuan Wu , Yu-Gang Jiang

Video face restoration aims to enhance degraded face videos into high-quality results with realistic facial details, stable identity, and temporal coherence. Recent diffusion-based methods have brought strong generative priors to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Zheng Chen , Bowen Chai , Rongjun Gao , Mingtao Nie , Xi Li , Bingnan Duan , Jianping Fang , Xiaohong Liu , Linghe Kong , Yulun 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

We introduce InstructVid2Vid, an end-to-end diffusion-based methodology for video editing guided by human language instructions. Our approach empowers video manipulation guided by natural language directives, eliminating the need for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Bosheng Qin , Juncheng Li , Siliang Tang , Tat-Seng Chua , Yueting Zhuang

Image diffusion distillation achieves high-fidelity generation with very few sampling steps. However, applying these techniques directly to video diffusion often results in unsatisfactory frame quality due to the limited visual quality in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Yuanhao Zhai , Kevin Lin , Zhengyuan Yang , Linjie Li , Jianfeng Wang , Chung-Ching Lin , David Doermann , Junsong Yuan , Lijuan Wang

Recent image-to-video (I2V) based video inpainting methods have made significant strides by leveraging single-image priors and modeling temporal consistency across masked frames. Nevertheless, these methods suffer from severe content…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Ming Xie , Junqiu Yu , Qiaole Dong , Xiangyang Xue , Yanwei Fu

In recent years, video generation has seen significant advancements. However, challenges still persist in generating complex motions and interactions. To address these challenges, we introduce ReVision, a plug-and-play framework that…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Qihao Liu , Ju He , Qihang Yu , Liang-Chieh Chen , Alan Yuille

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

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

Existing mobile devices are constrained by compact optical designs, such as small apertures, which make it difficult to produce natural, optically realistic bokeh effects. Although recent learning-based methods have shown promising results,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Linxiao Shi , Siming Zheng , Zerong Wang , Hao Zhang , Jinwei Chen , Bo Li , Shifeng Chen , Peng-Tao Jiang

Despite significant advancements in video generation and editing using diffusion models, achieving accurate and localized video editing remains a substantial challenge. Additionally, most existing video editing methods primarily focus on…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Chong Mou , Mingdeng Cao , Xintao Wang , Zhaoyang Zhang , Ying Shan , Jian Zhang

Consistent human-centric image and video synthesis aims to generate images or videos with new poses while preserving appearance consistency with a given reference image, which is crucial for low-cost visual content creation. Recent advances…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Mingdeng Cao , Chong Mou , Ziyang Yuan , Xintao Wang , Zhaoyang Zhang , Ying Shan , Yinqiang Zheng

Recent advances in deep generative modeling have unlocked unprecedented opportunities for video synthesis. In real-world applications, however, users often seek tools to faithfully realize their creative editing intentions with precise and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Yuhao Liu , Tengfei Wang , Fang Liu , Zhenwei Wang , Rynson W. H. Lau

Diffusion-based video generation techniques have significantly improved zero-shot talking-head avatar generation, enhancing the naturalness of both head motion and facial expressions. However, existing methods suffer from poor…

Graphics · Computer Science 2025-04-24 Lingzhou Mu , Baiji Liu , Ruonan Zhang , Guiming Mo , Jiawei Jin , Kai Zhang , Haozhi Huang

In this paper, we propose a novel diffusion-based multi-condition controllable framework for video head swapping, which seamlessly transplant a human head from a static image into a dynamic video, while preserving the original body and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Chaonan Ji , Jinwei Qi , Peng Zhang , Bang Zhang , Liefeng Bo