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Related papers: VMC: Video Motion Customization using Temporal Att…

200 papers

With recent advances in image and video diffusion models for content creation, a plethora of techniques have been proposed for customizing their generated content. In particular, manipulating the cross-attention layers of Text-to-Image…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Saman Motamed , Wouter Van Gansbeke , Luc Van Gool

The quadratic complexity of full attention mechanisms poses a significant bottleneck for Video Diffusion Models (VDMs) aiming to generate long-duration, high-resolution videos. While various sparse attention methods have been proposed, many…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Jianzong Wu , Liang Hou , Haotian Yang , Xin Tao , Ye Tian , Pengfei Wan , Di Zhang , Yunhai Tong

Diffusion models have demonstrated remarkable capabilities in text-to-image and text-to-video generation, opening up possibilities for video editing based on textual input. However, the computational cost associated with sequential sampling…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Youyuan Zhang , Xuan Ju , James J. Clark

Inspired by the impressive performance of recent face image editing methods, several studies have been naturally proposed to extend these methods to the face video editing task. One of the main challenges here is temporal consistency among…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Gyeongman Kim , Hajin Shim , Hyunsu Kim , Yunjey Choi , Junho Kim , Eunho Yang

Personalized text-to-image generation using diffusion models has recently emerged and garnered significant interest. This task learns a novel concept (e.g., a unique toy), illustrated in a handful of images, into a generative model that…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Shaozhe Hao , Kai Han , Shihao Zhao , Kwan-Yee K. Wong

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take advantage of various off-the-shelf 3D assets with multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yanqin Jiang , Chaohui Yu , Chenjie Cao , Fan Wang , Weiming Hu , Jin Gao

Video copy localization aims to precisely localize all the copied segments within a pair of untrimmed videos in video retrieval applications. Previous methods typically start from frame-to-frame similarity matrix generated by cosine…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Sifeng He , Yue He , Minlong Lu , Chen Jiang , Xudong Yang , Feng Qian , Xiaobo Zhang , Lei Yang , Jiandong Zhang

The correlation between the vision and text is essential for video moment retrieval (VMR), however, existing methods heavily rely on separate pre-training feature extractors for visual and textual understanding. Without sufficient temporal…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Dezhao Luo , Jiabo Huang , Shaogang Gong , Hailin Jin , Yang Liu

Video restoration (VR) aims to recover high-quality videos from degraded ones. Although recent zero-shot VR methods using pre-trained diffusion models (DMs) show good promise, they suffer from approximation errors during reverse diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Hengkang Wang , Yang Liu , Huidong Liu , Chien-Chih Wang , Yanhui Guo , Hongdong Li , Bryan Wang , Ju Sun

Consistency models have demonstrated powerful capability in efficient image generation and allowed synthesis within a few sampling steps, alleviating the high computational cost in diffusion models. However, the consistency model in the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Xiang Wang , Shiwei Zhang , Han Zhang , Yu Liu , Yingya Zhang , Changxin Gao , Nong Sang

Text-to-video (T2V) synthesis has gained increasing attention in the community, in which the recently emerged diffusion models (DMs) have promisingly shown stronger performance than the past approaches. While existing state-of-the-art DMs…

Artificial Intelligence · Computer Science 2024-03-20 Hao Fei , Shengqiong Wu , Wei Ji , Hanwang Zhang , Tat-Seng Chua

Video generation has drawn significant interest recently, pushing the development of large-scale models capable of producing realistic videos with coherent motion. Due to memory constraints, these models typically generate short video…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Idan Kligvasser , Regev Cohen , George Leifman , Ehud Rivlin , Michael Elad

This paper investigates a solution for enabling in-context capabilities of video diffusion transformers, with minimal tuning required for activation. Specifically, we propose a simple pipeline to leverage in-context generation:…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Zhengcong Fei , Di Qiu , Debang Li , Changqian Yu , Mingyuan Fan

The video generation field has witnessed rapid improvements with the introduction of recent diffusion models. While these models have successfully enhanced appearance quality, they still face challenges in generating coherent and natural…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Yaosi Hu , Zhenzhong Chen , Chong Luo

In this study, we present an efficient and effective approach for achieving temporally consistent synthetic-to-real video translation in videos of varying lengths. Our method leverages off-the-shelf conditional image diffusion models,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Ernie Chu , Shuo-Yen Lin , Jun-Cheng Chen

Recent years have seen a tremendous improvement in the quality of video generation and editing approaches. While several techniques focus on editing appearance, few address motion. Current approaches using text, trajectories, or bounding…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Manuel Kansy , Jacek Naruniec , Christopher Schroers , Markus Gross , Romann M. Weber

Significant advancements have been achieved in the realm of large-scale pre-trained text-to-video Diffusion Models (VDMs). However, previous methods either rely solely on pixel-based VDMs, which come with high computational costs, or on…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 David Junhao Zhang , Jay Zhangjie Wu , Jia-Wei Liu , Rui Zhao , Lingmin Ran , Yuchao Gu , Difei Gao , Mike Zheng Shou

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

Large video diffusion and flow models have achieved remarkable success in high-quality video generation, but their use in real-time interactive applications remains limited due to their inefficient multi-step sampling process. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Weili Nie , Julius Berner , Nanye Ma , Chao Liu , Saining Xie , Arash Vahdat