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Video generation is one of the most challenging tasks in Machine Learning and Computer Vision fields of study. In this paper, we tackle the text to video generation problem, which is a conditional form of video generation. Humans can…

Computer Vision and Pattern Recognition · Computer Science 2021-07-30 Amir Mazaheri , Mubarak Shah

We present VEnhancer, a generative space-time enhancement framework that improves the existing text-to-video results by adding more details in spatial domain and synthetic detailed motion in temporal domain. Given a generated low-quality…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Jingwen He , Tianfan Xue , Dongyang Liu , Xinqi Lin , Peng Gao , Dahua Lin , Yu Qiao , Wanli Ouyang , Ziwei Liu

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

We introduce a novel diffusion-based video generation method, generating a video showing multiple events given multiple individual sentences from the user. Our method does not require a large-scale video dataset since our method uses a…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Gyeongrok Oh , Jaehwan Jeong , Sieun Kim , Wonmin Byeon , Jinkyu Kim , Sungwoong Kim , Sangpil Kim

The objective of this work is to manipulate visual timelines (e.g. a video) through natural language instructions, making complex timeline editing tasks accessible to non-expert or potentially even disabled users. We call this task…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Alejandro Pardo , Jui-Hsien Wang , Bernard Ghanem , Josef Sivic , Bryan Russell , Fabian Caba Heilbron

The vision and language generative models have been overgrown in recent years. For video generation, various open-sourced models and public-available services have been developed to generate high-quality videos. However, these methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Yaofang Liu , Xiaodong Cun , Xuebo Liu , Xintao Wang , Yong Zhang , Haoxin Chen , Yang Liu , Tieyong Zeng , Raymond Chan , Ying Shan

Generating coherent and useful image/video scenes from a free-form textual description is technically a very difficult problem to handle. Textual description of the same scene can vary greatly from person to person, or sometimes even for…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Faria Huq , Nafees Ahmed , Anindya Iqbal

Vector graphics are widely used in digital art and highly favored by designers due to their scalability and layer-wise properties. However, the process of creating and editing vector graphics requires creativity and design expertise, making…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Peiying Zhang , Nanxuan Zhao , Jing Liao

In this paper, we propose a novel text-based talking-head video generation framework that synthesizes high-fidelity facial expressions and head motions in accordance with contextual sentiments as well as speech rhythm and pauses. To be…

Computer Vision and Pattern Recognition · Computer Science 2021-05-10 Lincheng Li , Suzhen Wang , Zhimeng Zhang , Yu Ding , Yixing Zheng , Xin Yu , Changjie Fan

Text-conditioned diffusion models have emerged as a promising tool for neural video generation. However, current models still struggle with intricate spatiotemporal prompts and often generate restricted or incorrect motion. To address these…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Long Lian , Baifeng Shi , Adam Yala , Trevor Darrell , Boyi Li

Visual Text Rendering (VTR) remains a critical challenge in text-to-image generation, where even advanced models frequently produce text with structural anomalies such as distortion, blurriness, and misalignment. However, we find that…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Hanshen Zhu , Yuliang Liu , Xuecheng Wu , An-Lan Wang , Hao Feng , Dingkang Yang , Chao Feng , Can Huang , Jingqun Tang , Xiang Bai

In this paper, we present VideoGen, a text-to-video generation approach, which can generate a high-definition video with high frame fidelity and strong temporal consistency using reference-guided latent diffusion. We leverage an…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Xin Li , Wenqing Chu , Ye Wu , Weihang Yuan , Fanglong Liu , Qi Zhang , Fu Li , Haocheng Feng , Errui Ding , Jingdong Wang

Sketching is inherently a sequential process, in which strokes are drawn in a meaningful order to explore and refine ideas. However, most generative models treat sketches as static images, overlooking the temporal structure that underlies…

Computer Vision and Pattern Recognition · Computer Science 2026-02-18 Hui Ren , Yuval Alaluf , Omer Bar Tal , Alexander Schwing , Antonio Torralba , Yael Vinker

This paper presents a multimodal framework that attempts to unify visual understanding and generation within a shared discrete semantic representation. At its core is the Text-Aligned Tokenizer (TA-Tok), which converts images into discrete…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Jiaming Han , Hao Chen , Yang Zhao , Hanyu Wang , Qi Zhao , Ziyan Yang , Hao He , Xiangyu Yue , Lu Jiang

Revolutionary advancements in text-to-image models have unlocked new dimensions for sophisticated content creation, such as text-conditioned image editing, enabling the modification of existing images based on textual guidance. This…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Haoyu Zheng , Wenqiao Zhang , Yaoke Wang , Juncheng Li , Zheqi Lv , Xin Min , Mengze Li , Dongping Zhang , Siliang Tang , Yueting Zhuang

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

Text-driven content creation has evolved to be a transformative technique that revolutionizes creativity. Here we study the task of text-driven human video generation, where a video sequence is synthesized from texts describing the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Yuming Jiang , Shuai Yang , Tong Liang Koh , Wayne Wu , Chen Change Loy , Ziwei Liu

In recent years, 3D Gaussian splatting has emerged as a powerful technique for 3D reconstruction and generation, known for its fast and high-quality rendering capabilities. To address these shortcomings, this paper introduces a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Xianglong He , Junyi Chen , Sida Peng , Di Huang , Yangguang Li , Xiaoshui Huang , Chun Yuan , Wanli Ouyang , Tong He

With the advancement of generative artificial intelligence, previous studies have achieved the task of generating aesthetic images from hand-drawn sketches, fulfilling the public's needs for drawing. However, these methods are limited to…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Lifan Jiang , Shuang Chen , Boxi Wu , Xiaotong Guan , Jiahui Zhang

Text animation serves as an expressive medium, transforming static communication into dynamic experiences by infusing words with motion to evoke emotions, emphasize meanings, and construct compelling narratives. Crafting animations that are…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Zichen Liu , Yihao Meng , Hao Ouyang , Yue Yu , Bolin Zhao , Daniel Cohen-Or , Huamin Qu