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Leveraging Stable Diffusion for the generation of personalized portraits has emerged as a powerful and noteworthy tool, enabling users to create high-fidelity, custom character avatars based on their specific prompts. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Siying Cui , Jia Guo , Xiang An , Jiankang Deng , Yongle Zhao , Xinyu Wei , Ziyong Feng

The text-driven image and video diffusion models have achieved unprecedented success in generating realistic and diverse content. Recently, the editing and variation of existing images and videos in diffusion-based generative models have…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Yuyang Zhao , Enze Xie , Lanqing Hong , Zhenguo Li , Gim Hee Lee

Videos for mobile devices become the most popular access to share and acquire information recently. For the convenience of users' creation, in this paper, we present a system, namely MobileVidFactory, to automatically generate vertical…

Computer Vision and Pattern Recognition · Computer Science 2023-08-01 Junchen Zhu , Huan Yang , Wenjing Wang , Huiguo He , Zixi Tuo , Yongsheng Yu , Wen-Huang Cheng , Lianli Gao , Jingkuan Song , Jianlong Fu , Jiebo Luo

Text-to-video (T2V) generation technology holds potential to transform multiple domains such as education, marketing, entertainment, and assistive technologies for individuals with visual or reading comprehension challenges, by creating…

Graphics · Computer Science 2025-10-07 Nilay Kumar , Priyansh Bhandari , G. Maragatham

State-of-the-arts text-to-image generation models such as Imagen and Stable Diffusion Model have succeed remarkable progresses in synthesizing high-quality, feature-rich images with high resolution guided by human text prompts. Since…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Ziyi Dong , Pengxu Wei , Liang Lin

Generating long videos that can show complex stories, like movie scenes from scripts, has great promise and offers much more than short clips. However, current methods that use autoregression with diffusion models often struggle because…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Guangcong Zheng , Jianlong Yuan , Bo Wang , Haoyang Huang , Guoqing Ma , Nan Duan

Diffusion-based models have achieved state-of-the-art performance on text-to-image synthesis tasks. However, one critical limitation of these models is the low fidelity of generated images with respect to the text description, such as…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Qiucheng Wu , Yujian Liu , Handong Zhao , Trung Bui , Zhe Lin , Yang Zhang , Shiyu Chang

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

Modeling and generating human reactions poses a significant challenge with broad applications for computer vision and human-computer interaction. Existing methods either treat multiple individuals as a single entity, directly generating…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Xiyan Xu , Sirui Xu , Yu-Xiong Wang , Liang-Yan Gui

Diffusion models have recently emerged as powerful tools for camera simulation, enabling both geometric transformations and realistic optical effects. Among these, image-based bokeh rendering has shown promising results, but diffusion for…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yang Yang , Siming Zheng , Qirui Yang , Jinwei Chen , Boxi Wu , Xiaofei He , Deng Cai , Bo Li , Peng-Tao Jiang

Text-driven diffusion models have unlocked unprecedented abilities in image generation, whereas their video counterpart still lags behind due to the excessive training cost of temporal modeling. Besides the training burden, the generated…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Yabo Zhang , Yuxiang Wei , Dongsheng Jiang , Xiaopeng Zhang , Wangmeng Zuo , Qi Tian

The recently developed discrete diffusion models perform extraordinarily well in the text-to-image task, showing significant promise for handling the multi-modality signals. In this work, we harness these traits and present a unified…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Minghui Hu , Chuanxia Zheng , Heliang Zheng , Tat-Jen Cham , Chaoyue Wang , Zuopeng Yang , Dacheng Tao , Ponnuthurai N. Suganthan

Despite the impressive progress of multimodal generative models, video-to-audio generation still suffers from limited performance and limits the flexibility to prioritize sound synthesis for specific objects within the scene. Conversely,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Yujin Jeong , Yunji Kim , Sanghyuk Chun , Jiyoung Lee

Text-to-image diffusion models have significantly improved the seamless integration of visual text into diverse image contexts. Recent approaches further improve control over font styles through fine-tuning with predefined font…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Myungkyu Koo , Subin Kim , Sangkyung Kwak , Jaehyun Nam , Seojin Kim , Jinwoo Shin

Current video diffusion models achieve impressive generation quality but struggle in interactive applications due to bidirectional attention dependencies. The generation of a single frame requires the model to process the entire sequence,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Tianwei Yin , Qiang Zhang , Richard Zhang , William T. Freeman , Fredo Durand , Eli Shechtman , Xun Huang

Diffusion models, such as Stable Diffusion, have shown incredible performance on text-to-image generation. Since text-to-image generation often requires models to generate visual concepts with fine-grained details and attributes specified…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Xuehai He , Weixi Feng , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , William Yang Wang , Xin Eric Wang

Generating videos guided by camera trajectories poses significant challenges in achieving consistency and generalizability, particularly when both camera and object motions are present. Existing approaches often attempt to learn these…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Guojun Lei , Chi Wang , Yikai Wang , Hong Li , Ying Song , Weiwei Xu

This paper introduces MultiBooth, a novel and efficient technique for multi-concept customization in image generation from text. Despite the significant advancements in customized generation methods, particularly with the success of…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Chenyang Zhu , Kai Li , Yue Ma , Chunming He , Xiu Li

Diffusion generative models have recently become a powerful technique for creating and modifying high-quality, coherent video content. This survey provides a comprehensive overview of the critical components of diffusion models for video…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Andrew Melnik , Michal Ljubljanac , Cong Lu , Qi Yan , Weiming Ren , Helge Ritter

Video editing methods based on diffusion models that rely solely on a text prompt for the edit are hindered by the limited expressive power of text prompts. Thus, incorporating a reference target image as a visual guide becomes desirable…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Sai Sree Harsha , Ambareesh Revanur , Dhwanit Agarwal , Shradha Agrawal
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