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Creating 3D character animations traditionally requires significant time and effort from the animator. Advancements in generative methods now enable easy creation of multiple character animation variations for use or further editing.…

Human-Computer Interaction · Computer Science 2026-05-05 Ludwig Sidenmark , Qian Zhou , George Fitzmaurice , Fraser Anderson

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

Comparing a user video to a reference how-to video is a key requirement for AR/VR technology delivering personalized assistance tailored to the user's progress. However, current approaches for language-based assistance can only answer…

Computer Vision and Pattern Recognition · Computer Science 2024-07-01 Tushar Nagarajan , Lorenzo Torresani

Video editing can be a very tedious task, so unsurprisingly Artificial Intelligence has been increasingly used to streamline the workflow or automate away tedious tasks. However, it is very difficult to get an overview of what intelligent…

Human-Computer Interaction · Computer Science 2021-09-17 Than Htut Soe

Creating novel images by fusing visual cues from multiple sources is a fundamental yet underexplored problem in image-to-image generation, with broad applications in artistic creation, virtual reality and visual media. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Zeren Xiong , Yue Yu , Zedong Zhang , Shuo Chen , Jian Yang , Jun Li

Video is a powerful medium for communication and storytelling, yet reauthoring existing footage remains challenging. Even simple edits often demand expertise, time, and careful planning, constraining how creators envision and shape their…

Human-Computer Interaction · Computer Science 2026-04-07 Sitong Wang , Anh Truong , Lydia B. Chilton , Dingzeyu Li

Video content creation keeps growing at an incredible pace; yet, creating engaging stories remains challenging and requires non-trivial video editing expertise. Many video editing components are astonishingly hard to automate primarily due…

Computer Vision and Pattern Recognition · Computer Science 2021-09-30 Alejandro Pardo , Fabian Caba Heilbron , Juan León Alcázar , Ali Thabet , Bernard Ghanem

Video diffusion models have recently achieved remarkable results in video generation. Despite their encouraging performance, most of these models are mainly designed and trained for short video generation, leading to challenges in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Zhuoling Li , Hossein Rahmani , Qiuhong Ke , Jun Liu

Visual dubbing, the synchronization of facial movements with new speech, is crucial for making content accessible across different languages, enabling broader global reach. However, current methods face significant limitations. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Binyamin Manela , Sharon Gannot , Ethan Fetyaya

Video summarization is a task of shortening a video by choosing a subset of frames while preserving its essential moments. Despite the innate subjectivity of the task, previous works have deterministically regressed to an averaged frame…

Machine Learning · Computer Science 2025-10-10 Kwanseok Kim , Jaehoon Hahm , Sumin Kim , Jinhwan Sul , Byunghak Kim , Joonseok Lee

Diffusion models have made tremendous progress in text-driven image and video generation. Now text-to-image foundation models are widely applied to various downstream image synthesis tasks, such as controllable image generation and image…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Fengyuan Shi , Jiaxi Gu , Hang Xu , Songcen Xu , Wei Zhang , Limin Wang

Generative models have made remarkable advancements and are capable of producing high-quality content. However, performing controllable editing with generative models remains challenging, due to their inherent uncertainty in outputs. This…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yikun Ma , Yiqing Li , Jiawei Wu , Xing Luo , Zhi Jin

Group portrait editing is highly desirable since users constantly want to add a person, delete a person, or manipulate existing persons. It is also challenging due to the intricate dynamics of human interactions and the diverse gestures. In…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Yuming Jiang , Nanxuan Zhao , Qing Liu , Krishna Kumar Singh , Shuai Yang , Chen Change Loy , Ziwei Liu

Audio description (AD) narrates visual elements in video for blind and low-vision audiences. Recent work has shown that giving novice describers an AI-generated draft to start from helps produce higher-quality AD and lowers the barrier to…

Human-Computer Interaction · Computer Science 2026-05-08 Lana Do , Shasta Ihorn , Charity M. Pitcher-Cooper , Sanjay Mirani , Gio Jung , Hyunjoo Shim , Zhenzhen Qin , Kien T. Nguyen , Vassilis Athitsos , Ilmi Yoon

Recent advancements in diffusion models have significantly facilitated text-guided video editing. However, there is a relative scarcity of research on image-guided video editing, a method that empowers users to edit videos by merely…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Zhi-Lin Huang , Yixuan Liu , Chujun Qin , Zhongdao Wang , Dong Zhou , Dong Li , Emad Barsoum

With the rapid development of generative technology, current generative models can generate high-fidelity digital content and edit it in a controlled manner. However, there is a risk that malicious individuals might misuse these…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Junjie Cao , Kaizhou Li , Xinchun Yu , Hongxiang Li , Xiaoping Zhang

Diffusion models, as a type of generative model, have achieved impressive results in generating images and videos conditioned on textual conditions. However, the generation process of diffusion models involves denoising dozens of steps to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Hui Zhang , Zuxuan Wu , Zhen Xing , Jie Shao , Yu-Gang Jiang

The diffusion model is widely leveraged for either video generation or video editing. As each field has its task-specific problems, it is difficult to merely develop a single diffusion for completing both tasks simultaneously. Video…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Haoyu Zhao , Tianyi Lu , Jiaxi Gu , Xing Zhang , Qingping Zheng , Zuxuan Wu , Hang Xu , Yu-Gang Jiang

As AI-generated video becomes increasingly pervasive across media platforms, the ability to reliably distinguish synthetic content from authentic footage has become both urgent and essential. Existing approaches have primarily treated this…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Yifeng Gao , Yifan Ding , Hongyu Su , Juncheng Li , Yunhan Zhao , Lin Luo , Zixing Chen , Li Wang , Xin Wang , Yixu Wang , Xingjun Ma , Yu-Gang Jiang

Video transition effects are widely used in video editing to connect shots for creating cohesive and visually appealing videos. However, it is challenging for non-professionals to choose best transitions due to the lack of cinematographic…

Computer Vision and Pattern Recognition · Computer Science 2022-07-28 Yaojie Shen , Libo Zhang , Kai Xu , Xiaojie Jin
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