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There is a rapidly growing interest in controlling consistency across multiple generated images using diffusion models. Among various methods, recent works have found that simply manipulating attention modules by concatenating features from…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Jiaojiao Fan , Haotian Xue , Qinsheng Zhang , Yongxin Chen

Deepfakes, synthetic images generated by deep learning algorithms, represent one of the biggest challenges in the field of Digital Forensics. The scientific community is working to develop approaches that can discriminate the origin of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Orazio Pontorno , Luca Guarnera , Sebastiano Battiato

Diffusion models have achieved remarkable success in image synthesis. However, addressing artifacts and unrealistic regions remains a critical challenge. We propose self-refining diffusion, a novel framework that enhances image generation…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Seoyeon Lee , Gwangyeol Yu , Chaewon Kim , Jonghyuk Park

Night imaging with modern smartphone cameras is troublesome due to low photon count and unavoidable noise in the imaging system. Directly adjusting exposure time and ISO ratings cannot obtain sharp and noise-free images at the same time in…

Computer Vision and Pattern Recognition · Computer Science 2022-07-15 Yuzhi Zhao , Yongzhe Xu , Qiong Yan , Dingdong Yang , Xuehui Wang , Lai-Man Po

Event cameras differ from conventional RGB cameras in that they produce asynchronous data sequences. While RGB cameras capture every frame at a fixed rate, event cameras only capture changes in the scene, resulting in sparse and…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Dan Yang , Mehmet Yamac

Event cameras have the potential to revolutionize vision systems with their high temporal resolution and dynamic range, yet they remain susceptible to lens flare, a fundamental optical artifact that causes severe degradation. In event…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Haiqian Han , Lingdong Kong , Jianing Li , Ao Liang , Chengtao Zhu , Jiacheng Lyu , Lai Xing Ng , Xiangyang Ji , Wei Tsang Ooi , Benoit R. Cottereau

Most of the standard image and video codecs are block-based and depending upon the compression ratio the compressed images/videos suffer from different distortions. At low ratios, blurriness is observed and as compression increases blocking…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Maryam Viqar , Athar A. Moinuddin , Ekram Khan , M. Ghanbari

The detection of cracks is a crucial task in monitoring structural health and ensuring structural safety. The manual process of crack detection is time-consuming and subjective to the inspectors. Several researchers have tried tackling this…

Computer Vision and Pattern Recognition · Computer Science 2022-08-30 Shreyas Kulkarni , Shreyas Singh , Dhananjay Balakrishnan , Siddharth Sharma , Saipraneeth Devunuri , Sai Chowdeswara Rao Korlapati

Detecting diffusion-generated images has recently grown into an emerging research area. Existing diffusion-based datasets predominantly focus on general image generation. However, facial forgeries, which pose a more severe social risk, have…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Harry Cheng , Yangyang Guo , Tianyi Wang , Liqiang Nie , Mohan Kankanhalli

Recent single-image relighting methods, powered by advanced generative models, have achieved impressive photorealism on synthetic benchmarks. However, their effectiveness in the complex visual landscape of the real world remains largely…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Lezhong Wang , Mehmet Onurcan Kaya , Siavash Bigdeli , Jeppe Revall Frisvad

Modern digital cameras rely on the sequential execution of separate image processing steps to produce realistic images. The first two steps are usually related to denoising and demosaicking where the former aims to reduce noise from the…

Computer Vision and Pattern Recognition · Computer Science 2019-04-02 Filippos Kokkinos , Stamatios Lefkimmiatis

High Dynamic Range (HDR) images can be recovered from several Low Dynamic Range (LDR) images by existing Deep Neural Networks (DNNs) techniques. Despite the remarkable progress, DNN-based methods still generate ghosting artifacts when LDR…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Qingsen Yan , Tao Hu , Yuan Sun , Hao Tang , Yu Zhu , Wei Dong , Luc Van Gool , Yanning Zhang

This paper deals with a challenging, frequently encountered, yet not properly investigated problem in two-frame optical flow estimation. That is, the input frames are compounds of two imaging layers -- one desired background layer of the…

Computer Vision and Pattern Recognition · Computer Science 2016-05-09 Jiaolong Yang , Hongdong Li , Yuchao Dai , Robby T. Tan

With the rapid advancement of generative models, highly realistic image synthesis has posed new challenges to digital security and media credibility. Although AI-generated image detection methods have partially addressed these concerns, a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Chunxiao Li , Xiaoxiao Wang , Meiling Li , Boming Miao , Peng Sun , Yunjian Zhang , Xiangyang Ji , Yao Zhu

In real-world environments, outdoor imaging systems are often affected by disturbances such as rain degradation. Especially, in nighttime driving scenes, insufficient and uneven lighting shrouds the scenes in darkness, resulting degradation…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Cidan Shi , Lihuang Fang , Han Wu , Xiaoyu Xian , Yukai Shi , Liang Lin

Despite remarkable achievements in video synthesis, achieving granular control over complex dynamics, such as nuanced movement among multiple interacting objects, still presents a significant hurdle for dynamic world modeling, compounded by…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Pengxiang Li , Kai Chen , Zhili Liu , Ruiyuan Gao , Lanqing Hong , Guo Zhou , Hua Yao , Dit-Yan Yeung , Huchuan Lu , Xu Jia

Making line segment detectors more reliable under motion blurs is one of the most important challenges for practical applications, such as visual SLAM and 3D reconstruction. Existing line segment detection methods face severe performance…

Computer Vision and Pattern Recognition · Computer Science 2024-10-28 Huai Yu , Hao Li , Wen Yang , Lei Yu , Gui-Song Xia

Ultra-high dynamic range (UHDR) scenes exhibit significant exposure disparities between bright and dark regions. Such conditions are commonly encountered in nighttime scenes with light sources. Even with standard exposure settings, a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Yuang Meng , Xin Jin , Lina Lei , Chun-Le Guo , Chongyi Li

Photosequencing aims to transform a motion blurred image to a sequence of sharp images. This problem is challenging due to the inherent ambiguities in temporal ordering as well as the recovery of lost spatial textures due to blur. Adopting…

Computer Vision and Pattern Recognition · Computer Science 2019-12-13 Vijay Rengarajan , Shuo Zhao , Ruiwen Zhen , John Glotzbach , Hamid Sheikh , Aswin C. Sankaranarayanan

Large-scale structures suffer high-frequency deformations due to complex loads. However, harsh lighting conditions and high equipment costs limit measurement methods based on traditional high-speed cameras. This paper proposes a method to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Yifei Bian , Banglei Guan , Zibin Liu , Ang Su , Shiyao Zhu , Yang Shang , Qifeng Yu
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