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Related papers: Video Generation Beyond a Single Clip

200 papers

Creation of images using generative adversarial networks has been widely adapted into multi-modal regime with the advent of multi-modal representation models pre-trained on large corpus. Various modalities sharing a common representation…

Sound · Computer Science 2022-06-10 Yoonjeon Kim , Joel Jang , Sumin Shin

Text-driven diffusion models have unlocked unprecedented abilities in image generation, whereas their video counterpart still lags behind due to the excessive training cost of temporal modeling. Besides the training burden, the generated…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Yabo Zhang , Yuxiang Wei , Dongsheng Jiang , Xiaopeng Zhang , Wangmeng Zuo , Qi Tian

Although recent end-to-end video generation models demonstrate impressive performance in visually oriented content creation, they remain limited in scenarios that require strict logical rigor and precise knowledge representation, such as…

Artificial Intelligence · Computer Science 2026-02-13 Lingyong Yan , Jiulong Wu , Dong Xie , Weixian Shi , Deguo Xia , Jizhou Huang

Video matting has traditionally been limited by the lack of high-quality ground-truth data. Most existing video matting datasets provide only human-annotated imperfect alpha and foreground annotations, which must be composited to background…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Yongtao Ge , Kangyang Xie , Guangkai Xu , Mingyu Liu , Li Ke , Longtao Huang , Hui Xue , Hao Chen , Chunhua Shen

The creation of diverse and realistic driving scenarios has become essential to enhance perception and planning capabilities of the autonomous driving system. However, generating long-duration, surround-view consistent driving videos…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Rui Chen , Zehuan Wu , Yichen Liu , Yuxin Guo , Jingcheng Ni , Haifeng Xia , Siyu Xia

Significant progress has been made in text-to-video generation through the use of powerful generative models and large-scale internet data. However, substantial challenges remain in precisely controlling individual concepts within the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Hanxin Zhu , Tianyu He , Anni Tang , Junliang Guo , Zhibo Chen , Jiang Bian

Video generation has been used to generate visual plans for controlling robotic systems. Given an image observation and a language instruction, previous work has generated video plans which are then converted to robot controls to be…

Artificial Intelligence · Computer Science 2025-02-11 Achint Soni , Sreyas Venkataraman , Abhranil Chandra , Sebastian Fischmeister , Percy Liang , Bo Dai , Sherry Yang

Millions of surveillance cameras operate at 24x7 generating huge amount of visual data for processing. However, retrieval of important activities from such a large data can be time consuming. Thus, researchers are working on finding…

Computer Vision and Pattern Recognition · Computer Science 2017-09-18 A. Ahmed , D. P. Dogra , S. Kar , R. Patnaik , S. Lee , H. Choi , I. Kim

Recent advancements in human video synthesis have enabled the generation of high-quality videos through the application of stable diffusion models. However, existing methods predominantly concentrate on animating solely the human element…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Jinlin Liu , Kai Yu , Mengyang Feng , Xiefan Guo , Miaomiao Cui

We present an efficient framework that can generate a coherent paragraph to describe a given video. Previous works on video captioning usually focus on video clips. They typically treat an entire video as a whole and generate the caption…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Yilei Xiong , Bo Dai , Dahua Lin

Video temporal grounding aims to pinpoint a video segment that matches the query description. Despite the recent advance in short-form videos (\textit{e.g.}, in minutes), temporal grounding in long videos (\textit{e.g.}, in hours) is still…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Yulin Pan , Xiangteng He , Biao Gong , Yiliang Lv , Yujun Shen , Yuxin Peng , Deli Zhao

360{\deg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the "tunnel vision" of standard cameras, their borderless field of view offers a more complete perspective of our surroundings. While…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Rundong Luo , Matthew Wallingford , Ali Farhadi , Noah Snavely , Wei-Chiu Ma

In order to perform unconditional video generation, we must learn the distribution of the real-world videos. In an effort to synthesize high-quality videos, various studies attempted to learn a mapping function between noise and videos,…

Computer Vision and Pattern Recognition · Computer Science 2021-12-22 Kangyeol Kim , Sunghyun Park , Junsoo Lee , Joonseok Lee , Sookyung Kim , Jaegul Choo , Edward Choi

Generating long videos that can show complex stories, like movie scenes from scripts, has great promise and offers much more than short clips. However, current methods that use autoregression with diffusion models often struggle because…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Guangcong Zheng , Jianlong Yuan , Bo Wang , Haoyang Huang , Guoqing Ma , Nan Duan

Recent advances in video generation have been driven by diffusion models and autoregressive frameworks, yet critical challenges persist in harmonizing prompt adherence, visual quality, motion dynamics, and duration: compromises in motion…

Research on diffusion model-based video generation has advanced rapidly. However, limitations in object fidelity and generation length hinder its practical applications. Additionally, specific domains like animated wallpapers require…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Fanyi Wang , Peng Liu , Haotian Hu , Dan Meng , Jingwen Su , Jinjin Xu , Yanhao Zhang , Xiaoming Ren , Zhiwang Zhang

Text-to-video diffusion models enable the generation of high-quality videos that follow text instructions, making it easy to create diverse and individual content. However, existing approaches mostly focus on high-quality short video…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Roberto Henschel , Levon Khachatryan , Hayk Poghosyan , Daniil Hayrapetyan , Vahram Tadevosyan , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

Multi-view or 4D video generation has emerged as a significant research topic. Nonetheless, recent approaches to 4D generation still struggle with fundamental limitations, as they primarily rely on harnessing multiple video diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Jangho Park , Taesung Kwon , Jong Chul Ye

Diffusion models have emerged as a powerful generative method for synthesizing high-quality and diverse set of images. In this paper, we propose a video generation method based on diffusion models, where the effects of motion are modeled in…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Kangfu Mei , Vishal M. Patel

Text-to-Video generation, which utilizes the provided text prompt to generate high-quality videos, has drawn increasing attention and achieved great success due to the development of diffusion models recently. Existing methods mainly rely…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Zirui Pan , Xin Wang , Yipeng Zhang , Hong Chen , Kwan Man Cheng , Yaofei Wu , Wenwu Zhu