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We present a framework for video modeling based on denoising diffusion probabilistic models that produces long-duration video completions in a variety of realistic environments. We introduce a generative model that can at test-time sample…

Computer Vision and Pattern Recognition · Computer Science 2022-12-19 William Harvey , Saeid Naderiparizi , Vaden Masrani , Christian Weilbach , Frank Wood

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

Recently, advancements in video synthesis have attracted significant attention. Video synthesis models such as AnimateDiff and Stable Video Diffusion have demonstrated the practical applicability of diffusion models in creating dynamic…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Zhongjie Duan , Wenmeng Zhou , Cen Chen , Yaliang Li , Weining Qian

Notable breakthroughs in unified understanding and generation modeling have led to remarkable advancements in image understanding, reasoning, production and editing, yet current foundational models predominantly focus on processing images,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Zhiyu Tan , Hao Yang , Luozheng Qin , Jia Gong , Mengping Yang , Hao Li

Diffusion models have recently achieved remarkable results for video generation. Despite the encouraging performances, the generated videos are typically constrained to a small number of frames, resulting in clips lasting merely a few…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Zhenxiong Tan , Xingyi Yang , Songhua Liu , Xinchao Wang

Video diffusion models have made substantial progress in various video generation applications. However, training models for long video generation tasks require significant computational and data resources, posing a challenge to developing…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Yu Lu , Yuanzhi Liang , Linchao Zhu , Yi Yang

Diffusion Transformers have demonstrated remarkable capabilities in visual synthesis, yet they often struggle with high-level semantic reasoning and long-horizon planning. This limitation frequently leads to visual hallucinations and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Lun Huang , You Xie , Hongyi Xu , Tianpei Gu , Chenxu Zhang , Guoxian Song , Zenan Li , Xiaochen Zhao , Linjie Luo , Guillermo Sapiro

Generating long-duration videos has always been a significant challenge due to the inherent complexity of spatio-temporal domain and the substantial GPU memory demands required to calculate huge size tensors. While diffusion based…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Siyang Zhang , Ser-Nam Lim

We address the problem of generating long-horizon videos for robotic manipulation tasks. Text-to-video diffusion models have made significant progress in photorealism, language understanding, and motion generation but struggle with…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Liudi Yang , Yang Bai , George Eskandar , Fengyi Shen , Mohammad Altillawi , Dong Chen , Soumajit Majumder , Ziyuan Liu , Gitta Kutyniok , Abhinav Valada

We present LingBot-World, an open-sourced world simulator stemming from video generation. Positioned as a top-tier world model, LingBot-World offers the following features. (1) It maintains high fidelity and robust dynamics in a broad…

Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuheng Liu , Xin Lin , Xinke Li , Baihan Yang , Chen Wang , Kalyan Sunkavalli , Yannick Hold-Geoffroy , Hao Tan , Kai Zhang , Xiaohui Xie , Zifan Shi , Yiwei Hu

The goal of this work is to generate step-by-step visual instructions in the form of a sequence of images, given an input image that provides the scene context and the sequence of textual instructions. This is a challenging problem as it…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Tomáš Souček , Prajwal Gatti , Michael Wray , Ivan Laptev , Dima Damen , Josef Sivic

Understanding the evolution of 3D scenes is important for effective autonomous driving. While conventional methods mode scene development with the motion of individual instances, world models emerge as a generative framework to describe the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Lening Wang , Wenzhao Zheng , Yilong Ren , Han Jiang , Zhiyong Cui , Haiyang Yu , Jiwen Lu

Human generation has achieved significant progress. Nonetheless, existing methods still struggle to synthesize specific regions such as faces and hands. We argue that the main reason is rooted in the training data. A holistic human dataset…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Jianglin Fu , Shikai Li , Yuming Jiang , Kwan-Yee Lin , Wayne Wu , Ziwei Liu

Generating realistic robotic manipulation videos is an important step toward unifying perception, planning, and action in embodied agents. While existing video diffusion models require large domain-specific datasets and struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Ye Pang

Video generation has been advancing rapidly, and diffusion transformer (DiT) based models have demonstrated remark- able capabilities. However, their practical deployment is of- ten hindered by slow inference speeds and high memory con-…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Sijie Wang , Qiang Wang , Shaohuai Shi

Achieving semantic alignment across diverse video generation conditions remains a significant challenge. Methods that rely on explicit structural guidance often enforce rigid spatial constraints that limit semantic flexibility, whereas…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Zexi Wu , Baolu Li , Jing Dai , Yiming Zhang , Yue Ma , Qinghe Wang , Xu Jia , Hongming Xu

Video generation models hold substantial potential in areas such as filmmaking. However, current video diffusion models need high computational costs and produce suboptimal results due to extreme complexity of video generation task. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Wenhao Li , Yichao Cao , Xiu Su , Xi Lin , Shan You , Mingkai Zheng , Yi Chen , Chang Xu

Producing long, coherent video sequences with stable 3D structure remains a major challenge, particularly in streaming scenarios. Motivated by this, we introduce Endless World, a real-time framework for infinite, 3D-consistent video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Ke Zhang , Yiqun Mei , Jiacong Xu , Vishal M. Patel

In ophthalmic surgery, developing an AI system capable of interpreting surgical videos and predicting subsequent operations requires numerous ophthalmic surgical videos with high-quality annotations, which are difficult to collect due to…

Image and Video Processing · Electrical Eng. & Systems 2025-07-15 Wei Li , Ming Hu , Guoan Wang , Lihao Liu , Kaijing Zhou , Junzhi Ning , Xin Guo , Zongyuan Ge , Lixu Gu , Junjun He