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This study presents Medical Vision Generalist (MVG), the first foundation model capable of handling various medical imaging tasks -- such as cross-modal synthesis, image segmentation, denoising, and inpainting -- within a unified…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Sucheng Ren , Xiaoke Huang , Xianhang Li , Junfei Xiao , Jieru Mei , Zeyu Wang , Alan Yuille , Yuyin Zhou

Medical generative models, acknowledged for their high-quality sample generation ability, have accelerated the fast growth of medical applications. However, recent works concentrate on separate medical generation models for distinct medical…

Image and Video Processing · Electrical Eng. & Systems 2024-03-08 Chenlu Zhan , Yu Lin , Gaoang Wang , Hongwei Wang , Jian Wu

Diffusion models have achieved impressive performance in video generation, but their iterative denoising process remains computationally expensive due to the large number of tokens processed at each timestep. Recently, progressive…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Shikang Zheng , Jingkai Huang , Jiacheng Liu , Guantao Chen , Lixuan , Yuqi Lin , Peiliang Cai , Linfeng Zhang

Leveraging text, images, structure maps, or motion trajectories as conditional guidance, diffusion models have achieved great success in automated and high-quality video generation. However, generating smooth and rational transition videos…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Zuhao Yang , Jiahui Zhang , Yingchen Yu , Shijian Lu , Song Bai

Disease progression simulation is a crucial area of research that has significant implications for clinical diagnosis, prognosis, and treatment. One major challenge in this field is the lack of continuous medical imaging monitoring of…

Image and Video Processing · Electrical Eng. & Systems 2023-10-06 Kaizhao Liang , Xu Cao , Kuei-Da Liao , Tianren Gao , Wenqian Ye , Zhengyu Chen , Jianguo Cao , Tejas Nama , Jimeng Sun

Long video generation remains a challenging and compelling topic in computer vision. Diffusion based models, among the various approaches to video generation, have achieved state of the art quality with their iterative denoising procedures.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Siyang Zhang , Harry Yang , Ser-Nam Lim

The creation of diverse and realistic driving scenarios has become essential to enhance perception and planning capabilities of the autonomous driving system. However, generating long-duration, surround-view consistent driving videos…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Rui Chen , Zehuan Wu , Yichen Liu , Yuxin Guo , Jingcheng Ni , Haifeng Xia , Siyu Xia

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

Recent diffusion methods have made significant progress in generating videos from single images due to their powerful visual generation capabilities. However, challenges persist in image-to-video synthesis, particularly in human video…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Tiantian Wang , Chun-Han Yao , Tao Hu , Mallikarjun Byrasandra Ramalinga Reddy , Ming-Hsuan Yang , Varun Jampani

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

Diffusion-based video generation models have made significant strides, producing outputs with improved visual fidelity, temporal coherence, and user control. These advancements hold great promise for improving surgical education by enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Joseph Cho , Samuel Schmidgall , Cyril Zakka , Mrudang Mathur , Dhamanpreet Kaur , Rohan Shad , William Hiesinger

Video diffusion models (VDMs) have advanced significantly in recent years, enabling the generation of highly realistic videos and drawing the attention of the community in their potential as world simulators. However, despite their…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Xindi Yang , Baolu Li , Yiming Zhang , Zhenfei Yin , Lei Bai , Liqian Ma , Zhiyong Wang , Jianfei Cai , Tien-Tsin Wong , Huchuan Lu , Xu Jia

The field of generative models has recently witnessed significant progress, with diffusion models showing remarkable performance in image generation. In light of this success, there is a growing interest in exploring the application of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Ariel Lapid , Idan Achituve , Lior Bracha , Ethan Fetaya

Medical video generation models are expected to have a profound impact on the healthcare industry, including but not limited to medical education and training, surgical planning, and simulation. Current video diffusion models typically…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Zhenbin Wang , Lei Zhang , Lituan Wang , Minjuan Zhu , Zhenwei Zhang

Human video generation task has gained significant attention with the advancement of deep generative models. Generating realistic videos with human movements is challenging in nature, due to the intricacies of human body topology and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Zhangsihao Yang , Mengyi Shan , Mohammad Farazi , Wenhui Zhu , Yanxi Chen , Xuanzhao Dong , Yalin Wang

Deep generative models have significantly advanced medical imaging analysis by enhancing dataset size and quality. Beyond mere data augmentation, our research in this paper highlights an additional, significant capacity of deep generative…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Xiaodan Xing , Junzhi Ning , Yang Nan , Guang Yang

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

Medical image segmentation models struggle with rare abnormalities due to scarce annotated pathological data. We propose DiffAug a novel framework that combines textguided diffusion-based generation with automatic segmentation validation to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Maham Nazir , Muhammad Aqeel , Francesco Setti

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

Vision-language models have demonstrated impressive capabilities in generating 2D images under various conditions; however, the success of these models is largely enabled by extensive, readily available pretrained foundation models.…

Image and Video Processing · Electrical Eng. & Systems 2025-10-02 Mohamed Mohamed , Brennan Nichyporuk , Douglas L. Arnold , Tal Arbel
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