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We tackle the long video generation problem, i.e.~generating videos beyond the output length of video generation models. Due to the computation resource constraints, video generation models can only generate video clips that are relatively…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Hsin-Ping Huang , Yu-Chuan Su , Ming-Hsuan Yang

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

Video diffusion models (VDMs) have advanced significantly in recent years, enabling the generation of highly realistic videos and drawing the attention of the community in their potential as world simulators. However, despite their…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Xindi Yang , Baolu Li , Yiming Zhang , Zhenfei Yin , Lei Bai , Liqian Ma , Zhiyong Wang , Jianfei Cai , Tien-Tsin Wong , Huchuan Lu , Xu Jia

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

World models, which predict future transitions from past observation and action sequences, have shown great promise for improving data efficiency in sequential decision-making. However, existing world models often require extensive…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Siqiao Huang , Jialong Wu , Qixing Zhou , Shangchen Miao , Mingsheng Long

Diffusion models have become a new generative paradigm for text generation. Considering the discrete categorical nature of text, in this paper, we propose GlyphDiffusion, a novel diffusion approach for text generation via text-guided image…

Computation and Language · Computer Science 2023-05-09 Junyi Li , Wayne Xin Zhao , Jian-Yun Nie , Ji-Rong Wen

Controllable video generation has attracted significant attention, largely due to advances in video diffusion models. In domains such as autonomous driving, it is essential to develop highly accurate predictions for object motions. This…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ge Ya Luo , Zhi Hao Luo , Anthony Gosselin , Alexia Jolicoeur-Martineau , Christopher Pal

Current deep learning results on video generation are limited while there are only a few first results on video prediction and no relevant significant results on video completion. This is due to the severe ill-posedness inherent in these…

Computer Vision and Pattern Recognition · Computer Science 2018-12-24 Haoye Cai , Chunyan Bai , Yu-Wing Tai , Chi-Keung Tang

Diffusion models exhibited tremendous progress in image and video generation, exceeding GANs in quality and diversity. However, they are usually trained on very large datasets and are not naturally adapted to manipulate a given input image…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Yaniv Nikankin , Niv Haim , Michal Irani

Diffusion-based text-to-image generation models like GLIDE and DALLE-2 have gained wide success recently for their superior performance in turning complex text inputs into images of high quality and wide diversity. In particular, they are…

Computer Vision and Pattern Recognition · Computer Science 2022-11-16 Zhihong Pan , Xin Zhou , Hao Tian

The task of music-driven dance generation involves creating coherent dance movements that correspond to the given music. While existing methods can produce physically plausible dances, they often struggle to generalize to out-of-set data.…

Sound · Computer Science 2024-11-12 Bo Han , Teng Zhang , Zeyu Ling , Yi Ren , Xiang Yin , Feilin Han

Controllable generation of 3D human motions becomes an important topic as the world embraces digital transformation. Existing works, though making promising progress with the advent of diffusion models, heavily rely on meticulously captured…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Nhat M. Hoang , Kehong Gong , Chuan Guo , Michael Bi Mi

Recent advances in text-to-video generation have harnessed the power of diffusion models to create visually compelling content conditioned on text prompts. However, they usually encounter high computational costs and often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Jiaxi Lv , Yi Huang , Mingfu Yan , Jiancheng Huang , Jianzhuang Liu , Yifan Liu , Yafei Wen , Xiaoxin Chen , Shifeng Chen

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

With the rise of online dance-video platforms and rapid advances in AI-generated content (AIGC), music-driven dance generation has emerged as a compelling research direction. Despite substantial progress in related domains such as…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Kaixing Yang , Jiashu Zhu , Xulong Tang , Ziqiao Peng , Xiangyue Zhang , Puwei Wang , Jiahong Wu , Xiangxiang Chu , Hongyan Liu , Jun He

Co-speech gestures, if presented in the lively form of videos, can achieve superior visual effects in human-machine interaction. While previous works mostly generate structural human skeletons, resulting in the omission of appearance…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xu He , Qiaochu Huang , Zhensong Zhang , Zhiwei Lin , Zhiyong Wu , Sicheng Yang , Minglei Li , Zhiyi Chen , Songcen Xu , Xiaofei Wu

Human motion generation aims to produce plausible human motion sequences according to various conditional inputs, such as text or audio. Despite the feasibility of existing methods in generating motion based on short prompts and simple…

Multimedia · Computer Science 2024-11-12 Bo Han , Hao Peng , Minjing Dong , Yi Ren , Yixuan Shen , Chang Xu

Recent years have seen significant progress in human image generation, particularly with the advancements in diffusion models. However, existing diffusion methods encounter challenges when producing consistent hand anatomy and the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Anton Pelykh , Ozge Mercanoglu Sincan , Richard Bowden

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

Recent progress in text-to-video generation has achieved remarkable realism, yet fine-grained control over camera motion and orientation remains elusive, especially with extreme trajectories (e.g., a 180-degree turnaround, or looking…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Frédéric Fortier-Chouinard , Yannick Hold-Geoffroy , Valentin Deschaintre , Matheus Gadelha , Jean-François Lalonde