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High-resolution (HR) medical videos are vital for accurate diagnosis, yet are hard to acquire due to hardware limitations and physiological constraints. Clinically, the collected low-resolution (LR) medical videos present unique challenges…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Xinyu Liu , Guolei Sun , Cheng Wang , Yixuan Yuan , Ender Konukoglu

In medical imaging, the diffusion models have shown great potential for synthetic image generation tasks. However, these approaches often lack the interpretable connections between the generated and real images and can create anatomically…

Image and Video Processing · Electrical Eng. & Systems 2026-02-12 Jian-Qing Zheng , Yuanhan Mo , Yang Sun , Jiahua Li , Fuping Wu , Ziyang Wang , Tonia Vincent , Bartłomiej W. Papież

Diffusion models have revolutionized generative modeling, enabling unprecedented realism in image and video synthesis. This success has sparked interest in leveraging their representations for visual understanding tasks. While recent works…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Pedro Vélez , Luisa F. Polanía , Yi Yang , Chuhan Zhang , Rishabh Kabra , Anurag Arnab , Mehdi S. M. Sajjadi

Video generation models have emerged as high-fidelity models of the physical world, capable of synthesizing high-quality videos capturing fine-grained interactions between agents and their environments conditioned on multi-modal user…

Most existing video diffusion models (VDMs) are limited to mere text conditions. Thereby, they are usually lacking in control over visual appearance and geometry structure of the generated videos. This work presents Moonshot, a new video…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 David Junhao Zhang , Dongxu Li , Hung Le , Mike Zheng Shou , Caiming Xiong , Doyen Sahoo

Diffusion-based video generation has achieved significant progress, yet generating multiple actions that occur sequentially remains a formidable task. Directly generating a video with sequential actions can be extremely challenging due to…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Bowen Zhang , Xiaofei Xie , Haotian Lu , Na Ma , Tianlin Li , Qing Guo

Masked generative models (MGMs) have shown impressive generative ability while providing an order of magnitude efficient sampling steps compared to continuous diffusion models. However, MGMs still underperform in image synthesis compared to…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Jiwan Hur , Dong-Jae Lee , Gyojin Han , Jaehyun Choi , Yunho Jeon , Junmo Kim

While diffusion model for audio-driven avatar video generation have achieved notable process in synthesizing long sequences with natural audio-visual synchronization and identity consistency, the generation of music-performance videos with…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Jiahui Chen , Weida Wang , Runhua Shi , Huan Yang , Chaofan Ding , Zihao Chen

Image-to-video generation, which aims to generate a video starting from a given reference image, has drawn great attention. Existing methods try to extend pre-trained text-guided image diffusion models to image-guided video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Songcen Xu , Hang Xu , Xiaodan Liang

Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

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

Data scarcity in medical imaging poses significant challenges due to privacy concerns. Diffusion models, a recent generative modeling technique, offer a potential solution by generating synthetic and realistic data. However, questions…

Image and Video Processing · Electrical Eng. & Systems 2024-12-24 Abdullah al Nomaan Nafi , Md. Alamgir Hossain , Rakib Hossain Rifat , Md Mahabub Uz Zaman , Md Manjurul Ahsan , Shivakumar Raman

Generating long and consistent videos has emerged as a significant yet challenging problem. While most existing diffusion-based video generation models, derived from image generation models, demonstrate promising performance in generating…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Yichen Ouyang , jianhao Yuan , Hao Zhao , Gaoang Wang , Bo zhao

With the advance of diffusion models, today's video generation has achieved impressive quality. But generating temporal consistent long videos is still challenging. A majority of video diffusion models (VDMs) generate long videos in an…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Kaifeng Gao , Jiaxin Shi , Hanwang Zhang , Chunping Wang , Jun Xiao

We introduce MVGenMaster, a multi-view diffusion model enhanced with 3D priors to address versatile Novel View Synthesis (NVS) tasks. MVGenMaster leverages 3D priors that are warped using metric depth and camera poses, significantly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Chenjie Cao , Chaohui Yu , Shang Liu , Fan Wang , Xiangyang Xue , Yanwei Fu

Diffusion models have gained tremendous success in text-to-image generation, yet still lag behind with visual understanding tasks, an area dominated by autoregressive vision-language models. We propose a large-scale and fully end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Zijie Li , Henry Li , Yichun Shi , Amir Barati Farimani , Yuval Kluger , Linjie Yang , Peng Wang

Recent advances in diffusion models have improved controllable streetscape generation and supported downstream perception and planning tasks. However, challenges remain in accurately modeling driving scenes and generating long videos. To…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Jianbiao Mei , Tao Hu , Xuemeng Yang , Licheng Wen , Yu Yang , Tiantian Wei , Yukai Ma , Min Dou , Botian Shi , Yong Liu

Recent video generation models have achieved remarkable progress and are now deployed in film, social media production, and advertising. Beyond their creative potential, such models also hold promise as world simulators for robotics and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 David Romero , Ariana Bermudez , Viacheslav Iablochnikov , Hao Li , Fabio Pizzati , Ivan Laptev

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…

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
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