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Related papers: MoViE: Mobile Diffusion for Video Editing

200 papers

Video diffusion generation suffers from critical sampling efficiency bottlenecks, particularly for large-scale models and long contexts. Existing video acceleration methods, adapted from image-based techniques, lack a single-step…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jiaxiang Cheng , Bing Ma , Xuhua Ren , Hongyi Henry Jin , Kai Yu , Peng Zhang , Wenyue Li , Yuan Zhou , Tianxiang Zheng , Qinglin Lu

This paper introduces V$^2$Edit, a novel training-free framework for instruction-guided video and 3D scene editing. Addressing the critical challenge of balancing original content preservation with editing task fulfillment, our approach…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Yanming Zhang , Jun-Kun Chen , Jipeng Lyu , Yu-Xiong Wang

Diffusion models have transformed the image-to-image (I2I) synthesis and are now permeating into videos. However, the advancement of video-to-video (V2V) synthesis has been hampered by the challenge of maintaining temporal consistency…

Computer Vision and Pattern Recognition · Computer Science 2024-01-01 Feng Liang , Bichen Wu , Jialiang Wang , Licheng Yu , Kunpeng Li , Yinan Zhao , Ishan Misra , Jia-Bin Huang , Peizhao Zhang , Peter Vajda , Diana Marculescu

Recent advances in diffusion models have revolutionized text-guided image editing, yet existing editing methods face critical challenges in hyperparameter identification. To get the reasonable editing performance, these methods often…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Chau Pham , Quan Dao , Mahesh Bhosale , Yunjie Tian , Dimitris Metaxas , David Doermann

Image customization has been extensively studied in text-to-image (T2I) diffusion models, leading to impressive outcomes and applications. With the emergence of text-to-video (T2V) diffusion models, its temporal counterpart, motion…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Yixuan Ren , Yang Zhou , Jimei Yang , Jing Shi , Difan Liu , Feng Liu , Mingi Kwon , Abhinav Shrivastava

Text-guided generative diffusion models unlock powerful image creation and editing tools. While these have been extended to video generation, current approaches that edit the content of existing footage while retaining structure require…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Patrick Esser , Johnathan Chiu , Parmida Atighehchian , Jonathan Granskog , Anastasis Germanidis

Recent advances in generative AI have significantly enhanced image and video editing, particularly in the context of text prompt control. State-of-the-art approaches predominantly rely on diffusion models to accomplish these tasks. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Haoyu Ma , Shahin Mahdizadehaghdam , Bichen Wu , Zhipeng Fan , Yuchao Gu , Wenliang Zhao , Lior Shapira , Xiaohui Xie

Text-driven video editing utilizing generative diffusion models has garnered significant attention due to their potential applications. However, existing approaches are constrained by the limited word embeddings provided in pre-training,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Mingce Guo , Jingxuan He , Shengeng Tang , Zhangye Wang , Lechao Cheng

We introduce TurboDiffusion, a video generation acceleration framework that can speed up end-to-end diffusion generation by 100-200x while maintaining video quality. TurboDiffusion mainly relies on several components for acceleration: (1)…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Jintao Zhang , Kaiwen Zheng , Kai Jiang , Haoxu Wang , Ion Stoica , Joseph E. Gonzalez , Jianfei Chen , Jun Zhu

Diffusion models have made significant advances in generating high-quality images, but their application to video generation has remained challenging due to the complexity of temporal motion. Zero-shot video editing offers a solution by…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Xirui Li , Chao Ma , Xiaokang Yang , Ming-Hsuan Yang

With deeper exploration of diffusion model, developments in the field of image generation have triggered a boom in image creation. As the quality of base-model generated images continues to improve, so does the demand for further…

Graphics · Computer Science 2025-04-21 Jia Wang , Jie Hu , Xiaoqi Ma , Hanghang Ma , Xiaoming Wei , Enhua Wu

Diffusion generative models have recently become a powerful technique for creating and modifying high-quality, coherent video content. This survey provides a comprehensive overview of the critical components of diffusion models for video…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Andrew Melnik , Michal Ljubljanac , Cong Lu , Qi Yan , Weiming Ren , Helge Ritter

The emergence of diffusion models has greatly broadened the scope of high-fidelity image synthesis, resulting in notable advancements in both practical implementation and academic research. With the active adoption of the model in various…

Machine Learning · Computer Science 2023-07-04 Jiwoong Choi , Minkyu Kim , Daehyun Ahn , Taesu Kim , Yulhwa Kim , Dongwon Jo , Hyesung Jeon , Jae-Joon Kim , Hyungjun Kim

Instruction-based video editing aims to modify an input video according to a natural-language instruction while preserving content fidelity and temporal coherence. However, existing diffusion-based approaches are often trained on paired…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Xiaoyan Cong , Haotian Yang , Angtian Wang , Yizhi Wang , Yiding Yang , Canyu Zhang , Chongyang Ma

Open-domain 3D object synthesis has been lagging behind image synthesis due to limited data and higher computational complexity. To bridge this gap, recent works have investigated multi-view diffusion but often fall short in either 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Hansheng Chen , Ruoxi Shi , Yulin Liu , Bokui Shen , Jiayuan Gu , Gordon Wetzstein , Hao Su , Leonidas Guibas

We introduce a novel diffusion-based video generation method, generating a video showing multiple events given multiple individual sentences from the user. Our method does not require a large-scale video dataset since our method uses a…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Gyeongrok Oh , Jaehwan Jeong , Sieun Kim , Wonmin Byeon , Jinkyu Kim , Sungwoong Kim , Sangpil Kim

Large pretrained diffusion models have significantly enhanced the quality of generated videos, and yet their use in real-time streaming remains limited. Autoregressive models offer a natural framework for sequential frame synthesis but…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Jinxiu Liu , Xuanming Liu , Kangfu Mei , Yandong Wen , Ming-Hsuan Yang , Weiyang Liu

GUI (graphical user interface) prototyping is a widely-used technique in requirements engineering for gathering and refining requirements, reducing development risks and increasing stakeholder engagement. However, GUI prototyping can be a…

Software Engineering · Computer Science 2023-10-05 Jialiang Wei , Anne-Lise Courbis , Thomas Lambolais , Binbin Xu , Pierre Louis Bernard , Gérard Dray

Diffusion models have emerged as the de facto paradigm for video generation. However, their reliance on web-scale data of varied quality often yields results that are visually unappealing and misaligned with the textual prompts. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Hangjie Yuan , Shiwei Zhang , Xiang Wang , Yujie Wei , Tao Feng , Yining Pan , Yingya Zhang , Ziwei Liu , Samuel Albanie , Dong Ni

With the increasing popularity of autonomous driving based on the powerful and unified bird's-eye-view (BEV) representation, a demand for high-quality and large-scale multi-view video data with accurate annotation is urgently required.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Xiaofan Li , Yifu Zhang , Xiaoqing Ye
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