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Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jinbo Xing , Menghan Xia , Yuxin Liu , Yuechen Zhang , Yong Zhang , Yingqing He , Hanyuan Liu , Haoxin Chen , Xiaodong Cun , Xintao Wang , Ying Shan , Tien-Tsin Wong

Recent research showcases the considerable potential of conditional diffusion models for generating consistent stories. However, current methods, which predominantly generate stories in an autoregressive and excessively caption-dependent…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Fei Shen , Hu Ye , Sibo Liu , Jun Zhang , Cong Wang , Xiao Han , Wei Yang

The rapid rise of image-to-video (I2V) generation enables realistic videos to be created from a single image but also brings new forensic demands. Unlike static images, I2V content evolves over time, requiring forensics to move beyond 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Yuzhuo Chen , Zehua Ma , Han Fang , Hengyi Wang , Guanjie Wang , Weiming Zhang

Text-to-video generation aims to produce a video based on a given prompt. Recently, several commercial video models have been able to generate plausible videos with minimal noise, excellent details, and high aesthetic scores. However, these…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Haoxin Chen , Yong Zhang , Xiaodong Cun , Menghan Xia , Xintao Wang , Chao Weng , Ying Shan

Text-to-video (T2V) generation is a rapidly growing research area that aims to translate the scenes, objects, and actions within complex video text into a sequence of coherent visual frames. We present FlowZero, a novel framework that…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Yu Lu , Linchao Zhu , Hehe Fan , Yi Yang

We present I2V3D, a novel framework for animating static images into dynamic videos with precise 3D control, leveraging the strengths of both 3D geometry guidance and advanced generative models. Our approach combines the precision of a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Zhiyuan Zhang , Dongdong Chen , Jing Liao

Diffusion models have achieved remarkable progress on image-to-video (I2V) generation, while their noise-to-data generation process is inherently mismatched with this task, which may lead to suboptimal synthesis quality. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Yuji Wang , Zehua Chen , Xiaoyu Chen , Yixiang Wei , Jun Zhu , Jianfei Chen

Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-to-video generation and propose a low-cost approach (without…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Levon Khachatryan , Andranik Movsisyan , Vahram Tadevosyan , Roberto Henschel , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

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

The intensive computational burden of Stable Diffusion (SD) for text-to-image generation poses a significant hurdle for its practical application. To tackle this challenge, recent research focuses on methods to reduce sampling steps, such…

Diffusion-based text-to-video generation (T2V) or image-to-video (I2V) generation have emerged as a prominent research focus. However, there exists a challenge in integrating the two generative paradigms into a unified model. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Xinyu Xiao , Binbin Yang , Tingtian Li , Yipeng Yu , Sen Lei

Sounding Video Generation (SVG) is an audio-video joint generation task challenged by high-dimensional signal spaces, distinct data formats, and different patterns of content information. To address these issues, we introduce a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Mingzhen Sun , Weining Wang , Yanyuan Qiao , Jiahui Sun , Zihan Qin , Longteng Guo , Xinxin Zhu , Jing Liu

Text-guided image-to-video (I2V) generation aims to generate a coherent video that preserves the identity of the input image and semantically aligns with the input prompt. Existing methods typically augment pretrained text-to-video (T2V)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Xun Guo , Mingwu Zheng , Liang Hou , Yuan Gao , Yufan Deng , Pengfei Wan , Di Zhang , Yufan Liu , Weiming Hu , Zhengjun Zha , Haibin Huang , Chongyang Ma

With the impressive progress in diffusion-based text-to-image generation, extending such powerful generative ability to text-to-video raises enormous attention. Existing methods either require large-scale text-video pairs and a large number…

Computer Vision and Pattern Recognition · Computer Science 2023-10-18 Ruiqi Wu , Liangyu Chen , Tong Yang , Chunle Guo , Chongyi Li , Xiangyu Zhang

Generative models that can model and predict sequences of future events can, in principle, learn to capture complex real-world phenomena, such as physical interactions. However, a central challenge in video prediction is that the future is…

Computer Vision and Pattern Recognition · Computer Science 2020-02-13 Manoj Kumar , Mohammad Babaeizadeh , Dumitru Erhan , Chelsea Finn , Sergey Levine , Laurent Dinh , Durk Kingma

Chinese landscape painting is a gem of Chinese cultural and artistic heritage that showcases the splendor of nature through the deep observations and imaginations of its painters. Limited by traditional techniques, these artworks were…

Multimedia · Computer Science 2024-04-22 Dingming Liu , Shaowei Li , Ruoyan Zhou , Lili Liang , Yongguan Hong , Fei Chao , Rongrong Ji

Diffusion models have achieved great success in image generation. However, when leveraging this idea for video generation, we face significant challenges in maintaining the consistency and continuity across video frames. This is mainly…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Haoran Lang , Yuxuan Ge , Zheng Tian

Modeling and forecasting subsurface multiphase fluid flow fields underpin applications ranging from geological CO2 sequestration (GCS) operations to geothermal production. This is essential for ensuring both operational performance and…

Machine Learning · Computer Science 2026-02-17 Vittoria De Pellegrini , Tariq Alkhalifah

Text-to-video (T2V) generation has been recently enabled by transformer-based diffusion models, but current T2V models lack capabilities in adhering to the real-world common knowledge and physical rules, due to their limited understanding…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Qiyao Xue , Xiangyu Yin , Boyuan Yang , Wei Gao

AI-generated content has attracted lots of attention recently, but photo-realistic video synthesis is still challenging. Although many attempts using GANs and autoregressive models have been made in this area, the visual quality and length…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Yingqing He , Tianyu Yang , Yong Zhang , Ying Shan , Qifeng Chen