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Diffusion-based text-to-video generation has witnessed impressive progress in the past year yet still falls behind text-to-image generation. One of the key reasons is the limited scale of publicly available data (e.g., 10M video-text pairs…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Xiang Wang , Shiwei Zhang , Hangjie Yuan , Zhiwu Qing , Biao Gong , Yingya Zhang , Yujun Shen , Changxin Gao , Nong Sang

While recent years have witnessed great progress on using diffusion models for video generation, most of them are simple extensions of image generation frameworks, which fail to explicitly consider one of the key differences between videos…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Jingyun Liang , Yuchen Fan , Kai Zhang , Radu Timofte , Luc Van Gool , Rakesh Ranjan

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

Customized generation using diffusion models has made impressive progress in image generation, but remains unsatisfactory in the challenging video generation task, as it requires the controllability of both subjects and motions. To that…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yujie Wei , Shiwei Zhang , Zhiwu Qing , Hangjie Yuan , Zhiheng Liu , Yu Liu , Yingya Zhang , Jingren Zhou , Hongming Shan

Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

Customized text-to-video generation aims to generate text-guided videos with user-given subjects, which has gained increasing attention. However, existing works are primarily limited to single-subject oriented text-to-video generation,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Hong Chen , Xin Wang , Guanning Zeng , Yipeng Zhang , Yuwei Zhou , Feilin Han , Yaofei Wu , Wenwu Zhu

With the emerging diffusion models, recently, text-to-video generation has aroused increasing attention. But an important bottleneck therein is that generative videos often tend to carry some flickers and artifacts. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Binhui Liu , Xin Liu , Anbo Dai , Zhiyong Zeng , Dan Wang , Zhen Cui , Jian Yang

Advances in technology have led to the development of methods that can create desired visual multimedia. In particular, image generation using deep learning has been extensively studied across diverse fields. In comparison, video…

Computer Vision and Pattern Recognition · Computer Science 2021-06-29 Doyeon Kim , Donggyu Joo , Junmo Kim

We present CogVideoX, a large-scale text-to-video generation model based on diffusion transformer, which can generate 10-second continuous videos aligned with text prompt, with a frame rate of 16 fps and resolution of 768 * 1360 pixels.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Zhuoyi Yang , Jiayan Teng , Wendi Zheng , Ming Ding , Shiyu Huang , Jiazheng Xu , Yuanming Yang , Wenyi Hong , Xiaohan Zhang , Guanyu Feng , Da Yin , Yuxuan Zhang , Weihan Wang , Yean Cheng , Bin Xu , Xiaotao Gu , Yuxiao Dong , Jie Tang

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new challenges posed by T2MVid generation lie in the lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Bing Li , Cheng Zheng , Wenxuan Zhu , Jinjie Mai , Biao Zhang , Peter Wonka , Bernard Ghanem

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

Our study introduces a new image-to-video generator called FashionFlow to generate fashion videos. By utilising a diffusion model, we are able to create short videos from still fashion images. Our approach involves developing and connecting…

Computer Vision and Pattern Recognition · Computer Science 2024-01-23 Tasin Islam , Alina Miron , XiaoHui Liu , Yongmin Li

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

Although humans have the innate ability to imagine multiple possible actions from videos, it remains an extraordinary challenge for computers due to the intricate camera movements and montages. Most existing motion generation methods…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Liangdong Qiu , Chengxing Yu , Yanran Li , Zhao Wang , Haibin Huang , Chongyang Ma , Di Zhang , Pengfei Wan , Xiaoguang Han

The deployment of large-scale text-to-image diffusion models on mobile devices is impeded by their substantial model size and slow inference speed. In this paper, we propose \textbf{MobileDiffusion}, a highly efficient text-to-image…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Yang Zhao , Yanwu Xu , Zhisheng Xiao , Haolin Jia , Tingbo Hou

We present an efficient text-to-video generation framework based on latent diffusion models, termed MagicVideo. MagicVideo can generate smooth video clips that are concordant with the given text descriptions. Due to a novel and efficient 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-05-12 Daquan Zhou , Weimin Wang , Hanshu Yan , Weiwei Lv , Yizhe Zhu , Jiashi Feng

Recent progress in diffusion-based video editing has shown remarkable potential for practical applications. However, these methods remain prohibitively expensive and challenging to deploy on mobile devices. In this study, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Adil Karjauv , Noor Fathima , Ioannis Lelekas , Fatih Porikli , Amir Ghodrati , Amirhossein Habibian

We present MicroCinema, a straightforward yet effective framework for high-quality and coherent text-to-video generation. Unlike existing approaches that align text prompts with video directly, MicroCinema introduces a Divide-and-Conquer…

Computer Vision and Pattern Recognition · Computer Science 2024-01-01 Yanhui Wang , Jianmin Bao , Wenming Weng , Ruoyu Feng , Dacheng Yin , Tao Yang , Jingxu Zhang , Qi Dai Zhiyuan Zhao , Chunyu Wang , Kai Qiu , Yuhui Yuan , Chuanxin Tang , Xiaoyan Sun , Chong Luo , Baining Guo

The generative AI revolution has recently expanded to videos. Nevertheless, current state-of-the-art video models are still lagging behind image models in terms of visual quality and user control over the generated content. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Michal Geyer , Omer Bar-Tal , Shai Bagon , Tali Dekel