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Discrete diffusion models have recently shown great promise for modeling complex discrete data, with masked diffusion models (MDMs) offering a compelling trade-off between quality and generation speed. MDMs denoise by progressively…

Machine Learning · Computer Science 2026-04-15 Tianyu Xie , Shuchen Xue , Zijin Feng , Tianyang Hu , Jiacheng Sun , Zhenguo Li , Cheng Zhang

Generating high-quality videos that synthesize desired realistic content is a challenging task due to their intricate high-dimensionality and complexity of videos. Several recent diffusion-based methods have shown comparable performance by…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Kihong Kim , Haneol Lee , Jihye Park , Seyeon Kim , Kwanghee Lee , Seungryong Kim , Jaejun Yoo

Inspired by the remarkable success of Latent Diffusion Models (LDMs) for image synthesis, we study LDM for text-to-video generation, which is a formidable challenge due to the computational and memory constraints during both model training…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Jiaxi Gu , Shicong Wang , Haoyu Zhao , Tianyi Lu , Xing Zhang , Zuxuan Wu , Songcen Xu , Wei Zhang , Yu-Gang Jiang , Hang Xu

With generative models producing high quality images that are indistinguishable from real ones, there is growing concern regarding the malicious usage of AI-generated images. Imperceptible image watermarking is one viable solution towards…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Ahmad Rezaei , Mohammad Akbari , Saeed Ranjbar Alvar , Arezou Fatemi , Yong Zhang

There has been tremendous progress in large-scale text-to-image synthesis driven by diffusion models enabling versatile downstream applications such as 3D object synthesis from texts, image editing, and customized generation. We present a…

Computer Vision and Pattern Recognition · Computer Science 2023-04-05 Ting-Hsuan Liao , Songwei Ge , Yiran Xu , Yao-Chih Lee , Badour AlBahar , Jia-Bin Huang

The target duration of a synthesized human motion is a critical attribute that requires modeling control over the motion dynamics and style. Speeding up an action performance is not merely fast-forwarding it. However, state-of-the-art…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Alessio Sampieri , Alessio Palma , Indro Spinelli , Fabio Galasso

We present a cascaded diffusion model based on a part-level implicit 3D representation. Our model achieves state-of-the-art generation quality and also enables part-level shape editing and manipulation without any additional training in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Juil Koo , Seungwoo Yoo , Minh Hieu Nguyen , Minhyuk Sung

Diffusion model is a promising approach to image generation and has been employed for Pose-Guided Person Image Synthesis (PGPIS) with competitive performance. While existing methods simply align the person appearance to the target pose,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Yanzuo Lu , Manlin Zhang , Andy J Ma , Xiaohua Xie , Jian-Huang Lai

We introduce Discrete Voxel Diffusion (DVD), a discrete diffusion framework to generate, assess, and edit sparse voxels for SLat (Structured LATent) based 3D generative pipelines. Although discrete diffusion has not generally displaced…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Zhengrui Xiang , Jiaqi Wu , Fupeng Sun , Heliang Zheng , Yingzhen Li

Low-field to high-field MRI synthesis has emerged as a cost-effective strategy to enhance image quality under hardware and acquisition constraints, particularly in scenarios where access to high-field scanners is limited or impractical.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Zhenxuan Zhang , Peiyuan Jing , Ruicheng Yuan , Liwei Hu , Anbang Wang , Fanwen Wang , Yinzhe Wu , Kh Tohidul Islam , Zhaolin Chen , Zi Wang , Peter Lally , Guang Yang

This paper introduces innovative solutions to enhance spatial controllability in diffusion models reliant on text queries. We first introduce vision guidance as a foundational spatial cue within the perturbed distribution. This…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zipeng Qi , Guoxi Huang , Chenyang Liu , Fei Ye

Diffusion models are successful for synthesizing high-quality videos but are limited to generating short clips (e.g., 2-10 seconds). Synthesizing sustained footage (e.g. over minutes) still remains an open research question. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Sihyun Yu , Meera Hahn , Dan Kondratyuk , Jinwoo Shin , Agrim Gupta , José Lezama , Irfan Essa , David Ross , Jonathan Huang

Latent Diffusion Models (LDMs) are renowned for their powerful capabilities in image and video synthesis. Yet, compared to text-to-image (T2I) editing, text-to-video (T2V) editing suffers from a lack of decent temporal consistency and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Tianyi Lu , Xing Zhang , Jiaxi Gu , Renjing Pei , Songcen Xu , Xingjun Ma , Hang Xu , Zuxuan Wu

Deep learning methods have impacted almost every research field, demonstrating notable successes in medical imaging tasks such as denoising and super-resolution. However, the prerequisite for deep learning is data at scale, but data sharing…

Medical Physics · Physics 2024-02-16 Yongyi Shi , Wenjun Xia , Chuang Niu , Christopher Wiedeman , Ge Wang

Diffusion models achieved great success in image synthesis, but still face challenges in high-resolution generation. Through the lens of discrete cosine transformation, we find the main reason is that \emph{the same noise level on a higher…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Jiayan Teng , Wendi Zheng , Ming Ding , Wenyi Hong , Jianqiao Wangni , Zhuoyi Yang , Jie Tang

Diffusion models have recently gained recognition for generating diverse and high-quality content, especially in image synthesis. These models excel not only in creating fixed-size images but also in producing panoramic images. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xiaoyu Zhang , Teng Zhou , Xinlong Zhang , Jia Wei , Yongchuan Tang

Diffusion models have become a mainstream approach for high-resolution image synthesis. However, directly generating higher-resolution images from pretrained diffusion models will encounter unreasonable object duplication and exponentially…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Shen Zhang , Zhaowei Chen , Zhenyu Zhao , Yuhao Chen , Yao Tang , Jiajun Liang

While consumer displays increasingly support more than 10 stops of dynamic range, most image assets such as internet photographs and generative AI content remain limited to 8-bit low dynamic range (LDR), constraining their utility across…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Chao Wang , Zhihao Xia , Thomas Leimkuehler , Karol Myszkowski , Xuaner Zhang

Latent diffusion models for image generation have crossed a quality threshold which enabled them to achieve mass adoption. Recently, a series of works have made advancements towards replicating this success in the 3D domain, introducing…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Anchit Gupta , Wenhan Xiong , Yixin Nie , Ian Jones , Barlas Oğuz

Latent diffusion models have become the popular choice for scaling up diffusion models for high resolution image synthesis. Compared to pixel-space models that are trained end-to-end, latent models are perceived to be more efficient and to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Emiel Hoogeboom , Thomas Mensink , Jonathan Heek , Kay Lamerigts , Ruiqi Gao , Tim Salimans
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