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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

With the advance of diffusion models, today's video generation has achieved impressive quality. To extend the generation length and facilitate real-world applications, a majority of video diffusion models (VDMs) generate videos in an…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Kaifeng Gao , Jiaxin Shi , Hanwang Zhang , Chunping Wang , Jun Xiao , Long Chen

With the advancement of interactive video generation, diffusion models have increasingly demonstrated their potential as world models. However, existing approaches still struggle to simultaneously achieve memory-enabled long-term temporal…

Text-driven motion generation has achieved substantial progress with the emergence of diffusion models. However, existing methods still struggle to generate complex motion sequences that correspond to fine-grained descriptions, depicting…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Mingyuan Zhang , Huirong Li , Zhongang Cai , Jiawei Ren , Lei Yang , Ziwei Liu

Autoregressive (AR) diffusion offers a promising framework for generating videos of theoretically infinite length. However, a major challenge is maintaining temporal continuity while preventing the progressive quality degradation caused by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Kai Zou , Dian Zheng , Hongbo Liu , Tiankai Hang , Bin Liu , Nenghai Yu

World models aim to endow AI systems with the ability to represent, generate, and interact with dynamic environments in a coherent and temporally consistent manner. While recent video generation models have demonstrated impressive visual…

Autoregressive video diffusion models enable streaming generation, opening the door to long-form synthesis, video world models, and interactive neural game engines. However, their core attention layers become a major bottleneck at inference…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Dvir Samuel , Issar Tzachor , Matan Levy , Micahel Green , Gal Chechik , Rami Ben-Ari

Generative models have been widely applied to world modeling for environment simulation and future state prediction. With advancements in autonomous driving, there is a growing demand not only for high-fidelity video generation under…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Tianrui Zhang , Yichen Liu , Zilin Guo , Yuxin Guo , Jingcheng Ni , Chenjing Ding , Dan Xu , Lewei Lu , Zehuan Wu

This study presents a novel method for generating music visualisers using diffusion models, combining audio input with user-selected artwork. The process involves two main stages: image generation and video creation. First, music captioning…

Multimedia · Computer Science 2024-12-10 Leonardo Pina , Yongmin Li

High dynamic range (HDR) video reconstruction aims to generate HDR videos from low dynamic range (LDR) frames captured with alternating exposures. Most existing works solely rely on the regression-based paradigm, leading to adverse effects…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Yuanshen Guan , Ruikang Xu , Mingde Yao , Ruisheng Gao , Lizhi Wang , Zhiwei Xiong

With recent advancements in video backbone architectures, combined with the remarkable achievements of large language models (LLMs), the analysis of long-form videos spanning tens of minutes has become both feasible and increasingly…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Yuxiao Chen , Jue Wang , Zhikang Zhang , Jingru Yi , Xu Zhang , Yang Zou , Zhaowei Cai , Jianbo Yuan , Xinyu Li , Hao Yang , Davide Modolo

Recent advances in the diffusion models have significantly improved text-to-image generation. However, generating videos from text is a more challenging task than generating images from text, due to the much larger dataset and higher…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Taegyeong Lee , Soyeong Kwon , Taehwan Kim

Text-to-motion generation has advanced rapidly, yet two challenges persist. First, existing motion autoencoders compress each frame into a single monolithic latent vector, entangling trajectory and per-joint rotations in an unstructured…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Zeyu Ling , Qing Shuai , Teng Zhang , Shiyang Li , Bo Han , Changqing Zou

Multi-shot video generation is crucial for long narrative storytelling, yet current bidirectional architectures suffer from limited interactivity and high latency. We propose ShotStream, a novel causal multi-shot architecture that enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Yawen Luo , Xiaoyu Shi , Junhao Zhuang , Yutian Chen , Quande Liu , Xintao Wang , Pengfei Wan , Tianfan Xue

Recent advancements in image generation have made significant progress, yet existing models present limitations in perceiving and generating an arbitrary number of interrelated images within a broad context. This limitation becomes…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Ying Shen , Yizhe Zhang , Shuangfei Zhai , Lifu Huang , Joshua M. Susskind , Jiatao Gu

Video dataset condensation aims to reduce the immense computational cost of video processing. However, it faces a fundamental challenge regarding the inseparable interdependence between spatial appearance and temporal dynamics. Prior work…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Jaehyun Choi , Jiwan Hur , Gyojin Han , Jaemyung Yu , Junmo Kim

Scaling multimodal large language models (MLLMs) to long videos is constrained by limited context windows. While retrieval-augmented generation (RAG) is a promising remedy by organizing query-relevant visual evidence into a compact context,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Honghao Fu , Miao Xu , Yiwei Wang , Dailing Zhang , Jun Liu , Yujun Cai

Multistep instructions, such as recipes and how-to guides, greatly benefit from visual aids, such as a series of images that accompany the instruction steps. While Large Language Models (LLMs) have become adept at generating coherent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 João Bordalo , Vasco Ramos , Rodrigo Valério , Diogo Glória-Silva , Yonatan Bitton , Michal Yarom , Idan Szpektor , Joao Magalhaes

Panoramic video generation aims to synthesize 360-degree immersive videos, holding significant importance in the fields of VR, world models, and spatial intelligence. Existing works fail to synthesize high-quality panoramic videos due to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zixun Fang , Kai Zhu , Zhiheng Liu , Yu Liu , Wei Zhai , Yang Cao , Zheng-Jun Zha

Despite recent advances in retrieval-augmented generation (RAG) for video understanding, effectively understanding long-form video content remains underexplored due to the vast scale and high complexity of video data. Current RAG approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Nianbo Zeng , Haowen Hou , Fei Richard Yu , Si Shi , Ying Tiffany He