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The lack of real-world data in clinical fields poses a major obstacle in training effective AI models for diagnostic and preventive tools in medicine. Generative AI has shown promise in increasing data volume and enhancing model training,…

Machine Learning · Computer Science 2026-02-10 Md Shahriar Kabir , Sana Alamgeer , Minakshi Debnath , Anne H. H. Ngu

Recent progress in generative AI, especially diffusion models, has demonstrated significant utility in text-to-image synthesis. Particularly in healthcare, these models offer immense potential in generating synthetic datasets and training…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yan Luo , Muhammad Osama Khan , Congcong Wen , Muhammad Muneeb Afzal , Titus Fidelis Wuermeling , Min Shi , Yu Tian , Yi Fang , Mengyu Wang

The generative model has made significant advancements in the creation of realistic videos, which causes security issues. However, this emerging risk has not been adequately addressed due to the absence of a benchmark dataset for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Peisong He , Leyao Zhu , Jiaxing Li , Shiqi Wang , Haoliang Li

Diffusion-based generative models have demonstrated exceptional promise in the video super-resolution (VSR) task, achieving a substantial advancement in detail generation relative to prior methods. However, these approaches face significant…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zhongdao Wang , Guodongfang Zhao , Jingjing Ren , Bailan Feng , Shifeng Zhang , Wenbo Li

Recent advances in computer vision have shown promising results in image generation. Diffusion probabilistic models in particular have generated realistic images from textual input, as demonstrated by DALL-E 2, Imagen and Stable Diffusion.…

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

The rapid advancement of Artificial Intelligence (AI) has catalyzed revolutionary changes across various sectors, notably in healthcare. In particular, generative AI-led by diffusion models and transformer architectures-has enabled…

Co-speech gestures, if presented in the lively form of videos, can achieve superior visual effects in human-machine interaction. While previous works mostly generate structural human skeletons, resulting in the omission of appearance…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xu He , Qiaochu Huang , Zhensong Zhang , Zhiwei Lin , Zhiyong Wu , Sicheng Yang , Minglei Li , Zhiyi Chen , Songcen Xu , Xiaofei Wu

The advent of text-to-video generation models has revolutionized content creation as it produces high-quality videos from textual prompts. However, concerns regarding inherent biases in such models have prompted scrutiny, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Mohammad Nadeem , Shahab Saquib Sohail , Erik Cambria , Björn W. Schuller , Amir Hussain

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

Diffusion models arise as a powerful generative tool recently. Despite the great progress, existing diffusion models mainly focus on uni-modal control, i.e., the diffusion process is driven by only one modality of condition. To further…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Ziqi Huang , Kelvin C. K. Chan , Yuming Jiang , Ziwei Liu

Modern video codecs and learning-based approaches struggle for semantic reconstruction at extremely low bit-rates due to reliance on low-level spatiotemporal redundancies. Generative models, especially diffusion models, offer a new paradigm…

Image and Video Processing · Electrical Eng. & Systems 2026-02-06 Maojun Zhang , Haotian Wu , Richeng Jin , Deniz Gunduz , Krystian Mikolajczyk

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…

The generation of medical images presents significant challenges due to their high-resolution and three-dimensional nature. Existing methods often yield suboptimal performance in generating high-quality 3D medical images, and there is…

Image and Video Processing · Electrical Eng. & Systems 2025-12-02 Haoshen Wang , Zhentao Liu , Kaicong Sun , Xiaodong Wang , Dinggang Shen , Zhiming Cui

Learning a generalist embodied agent capable of completing multiple tasks poses challenges, primarily stemming from the scarcity of action-labeled robotic datasets. In contrast, a vast amount of human videos exist, capturing intricate tasks…

Machine Learning · Computer Science 2024-10-10 Haoran He , Chenjia Bai , Ling Pan , Weinan Zhang , Bin Zhao , Xuelong Li

In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos. Specifically, given target identity and posture sequences, DreaMoving can generate a video of…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Mengyang Feng , Jinlin Liu , Kai Yu , Yuan Yao , Zheng Hui , Xiefan Guo , Xianhui Lin , Haolan Xue , Chen Shi , Xiaowen Li , Aojie Li , Xiaoyang Kang , Biwen Lei , Miaomiao Cui , Peiran Ren , Xuansong Xie

Diffusion models have been shown to implicitly generate visual content autoregressively in the frequency domain, where low-frequency components are generated earlier in the denoising process while high-frequency details emerge only in later…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Howard Xiao , Brian Chao , Lior Yariv , Gordon Wetzstein

Personalized text-to-image models allow users to generate varied styles of images (specified with a sentence) for an object (specified with a set of reference images). While remarkable results have been achieved using diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Fanyue Wei , Wei Zeng , Zhenyang Li , Dawei Yin , Lixin Duan , Wen Li

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

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
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