English
Related papers

Related papers: VideoCrafter1: Open Diffusion Models for High-Qual…

200 papers

In this study, we aim to enhance the capabilities of diffusion-based text-to-image (T2I) generation models by integrating diverse modalities beyond textual descriptions within a unified framework. To this end, we categorize widely used…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Sungnyun Kim , Junsoo Lee , Kibeom Hong , Daesik Kim , Namhyuk Ahn

We present Stable Video Diffusion - a latent video diffusion model for high-resolution, state-of-the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained for 2D image synthesis have been turned into…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Andreas Blattmann , Tim Dockhorn , Sumith Kulal , Daniel Mendelevitch , Maciej Kilian , Dominik Lorenz , Yam Levi , Zion English , Vikram Voleti , Adam Letts , Varun Jampani , Robin Rombach

Text-to-video (T2V) diffusion models have achieved rapid progress, yet their demographic biases, particularly gender bias, remain largely unexplored. We present FairT2V, a training-free debiasing framework for text-to-video generation that…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Haonan Zhong , Wei Song , Tingxu Han , Maurice Pagnucco , Jingling Xue , Yang Song

Large-scale generative models, such as text-to-image diffusion models, have garnered widespread attention across diverse domains due to their creative and high-fidelity image generation. Nonetheless, existing large-scale diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Younghyun Kim , Geunmin Hwang , Junyu Zhang , Eunbyung Park

The text-to-video (T2V) generation models, offering convenient visual creation, have recently garnered increasing attention. Despite their substantial potential, the generated videos may present artifacts, including structural…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Jiazi Bu , Pengyang Ling , Pan Zhang , Tong Wu , Xiaoyi Dong , Yuhang Zang , Yuhang Cao , Dahua Lin , Jiaqi Wang

Transition videos play a crucial role in media production, enhancing the flow and coherence of visual narratives. Traditional methods like morphing often lack artistic appeal and require specialized skills, limiting their effectiveness.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Rui Zhang , Yaosen Chen , Yuegen Liu , Wei Wang , Xuming Wen , Hongxia Wang

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

Video generation has achieved remarkable progress with the introduction of diffusion models, which have significantly improved the quality of generated videos. However, recent research has primarily focused on scaling up model training,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Chenyang Si , Weichen Fan , Zhengyao Lv , Ziqi Huang , Yu Qiao , Ziwei Liu

Video generation is an inherently challenging task, as it requires modeling realistic temporal dynamics as well as spatial content. Existing methods entangle the two intrinsically different tasks of motion and content creation in a single…

Computer Vision and Pattern Recognition · Computer Science 2020-01-13 Ximeng Sun , Huijuan Xu , Kate Saenko

Text-to-image generation has made remarkable progress with the emergence of diffusion models. However, it is still a difficult task to generate images for street views based on text, mainly because the road topology of street scenes is…

Computer Vision and Pattern Recognition · Computer Science 2024-02-08 Jinming Su , Songen Gu , Yiting Duan , Xingyue Chen , Junfeng Luo

In this study, we explore Transformer-based diffusion models for image and video generation. Despite the dominance of Transformer architectures in various fields due to their flexibility and scalability, the visual generative domain…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Shoufa Chen , Mengmeng Xu , Jiawei Ren , Yuren Cong , Sen He , Yanping Xie , Animesh Sinha , Ping Luo , Tao Xiang , Juan-Manuel Perez-Rua

Large-scale, pre-trained Text-to-Image (T2I) diffusion models have gained significant popularity in image generation tasks and have shown unexpected potential in image Super-Resolution (SR). However, most existing T2I diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Brian B. Moser , Stanislav Frolov , Tobias C. Nauen , Federico Raue , Andreas Dengel

This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts with a brief introduction of how diffusion models work for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Chenshuang Zhang , Chaoning Zhang , Mengchun Zhang , In So Kweon , Junmo Kim

The recent wave of AI-generated content (AIGC) has witnessed substantial success in computer vision, with the diffusion model playing a crucial role in this achievement. Due to their impressive generative capabilities, diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Zhen Xing , Qijun Feng , Haoran Chen , Qi Dai , Han Hu , Hang Xu , Zuxuan Wu , Yu-Gang Jiang

Instructional video editing applies edits to an input video using only text prompts, enabling intuitive natural-language control. Despite rapid progress, most methods still require fixed-length inputs and substantial compute. Meanwhile,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Mohammadreza Salehi , Mehdi Noroozi , Luca Morreale , Ruchika Chavhan , Malcolm Chadwick , Alberto Gil Ramos , Abhinav Mehrotra

Generative modeling is widely regarded as one of the most essential problems in today's AI community, with text-to-image generation having gained unprecedented real-world impacts. Among various approaches, diffusion models have achieved…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xuyang Guo , Jiayan Huo , Yingyu Liang , Zhenmei Shi , Zhao Song , Jiahao Zhang , Zhen Zhuang

Text-to-image (T2I) generative diffusion models have demonstrated outstanding performance in synthesizing diverse, high-quality visuals from text captions. Several layout-to-image models have been developed to control the generation process…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Ahmad Süleyman , Göksel Biricik

While generative models such as text-to-image, large language models and text-to-video have seen significant progress, the extension to text-to-virtual-reality remains largely unexplored, due to a deficit in training data and the complexity…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Vriksha Srihari , R. Bhavya , Shruti Jayaraman , V. Mary Anita Rajam

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

Diffusion based video generation has received extensive attention and achieved considerable success within both the academic and industrial communities. However, current efforts are mainly concentrated on single-objective or single-task…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Ludan Ruan , Lei Tian , Chuanwei Huang , Xu Zhang , Xinyan Xiao