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Facial recognition technology (FRT) is increasingly used in criminal investigations, yet most evaluations of its accuracy rely on high-quality images, unlike those often encountered by law enforcement. This study examines how five common…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Maria Cuellar , Hon Kiu , To , Arush Mehrotra

There is widespread interest in estimating the fluorescence properties of natural materials in an image. However, the separation between reflected and fluoresced components is difficult, because it is impossible to distinguish reflected and…

Computer Vision and Pattern Recognition · Computer Science 2016-05-16 Henryk Blasinski , Joyce Farrell , Brian Wandell

Recent advances in deep learning have significantly increased the performance of face recognition systems. The performance and reliability of these models depend heavily on the amount and quality of the training data. However, the…

Computer Vision and Pattern Recognition · Computer Science 2018-02-19 Adam Kortylewski , Andreas Schneider , Thomas Gerig , Bernhard Egger , Andreas Morel-Forster , Thomas Vetter

This paper considers image change detection with only a small number of samples, which is a significant problem in terms of a few annotations available. A major impediment of image change detection task is the lack of large annotated…

Computer Vision and Pattern Recognition · Computer Science 2023-11-08 Ke Liu , Zhaoyi Song , Haoyue Bai

Multi-focus image fusion, a technique to generate an all-in-focus image from two or more partially-focused source images, can benefit many computer vision tasks. However, currently there is no large and realistic dataset to perform…

Computer Vision and Pattern Recognition · Computer Science 2020-08-31 Juncheng Zhang , Qingmin Liao , Shaojun Liu , Haoyu Ma , Wenming Yang , Jing-Hao Xue

Shadows can originate from occlusions in both direct and indirect illumination. Although most current shadow removal research focuses on shadows caused by direct illumination, shadows from indirect illumination are often just as pervasive,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Jiamin Xu , Zelong Li , Yuxin Zheng , Chenyu Huang , Renshu Gu , Weiwei Xu , Gang Xu

Reflection removal of a single image remains a highly challenging task due to the complex entanglement between target scenes and unwanted reflections. Despite significant progress, existing methods are hindered by the scarcity of…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Jichen Hu , Chen Yang , Zanwei Zhou , Jiemin Fang , Xiaokang Yang , Qi Tian , Wei Shen

Nighttime image dehazing faces a more complex degradation pattern than its daytime counterpart, as haze scattering couples with low illumination, non-uniform lighting, and strong light interference. Under limited supervision, this…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Xining Ge , Weijun Yuan , Gengjia Chang , Xuyang Li , Shuhong Liu

We present a novel formulation to removing reflection from polarized images in the wild. We first identify the misalignment issues of existing reflection removal datasets where the collected reflection-free images are not perfectly aligned…

Computer Vision and Pattern Recognition · Computer Science 2020-03-31 Chenyang Lei , Xuhua Huang , Mengdi Zhang , Qiong Yan , Wenxiu Sun , Qifeng Chen

Low-light image enhancement is crucial for a myriad of applications, from night vision and surveillance, to autonomous driving. However, due to the inherent limitations that come in hand with capturing images in low-illumination…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Manjushree Aithal , Rosaura G. VidalMata , Manikandtan Kartha , Gong Chen , Eashan Adhikarla , Lucas N. Kirsten , Zhicheng Fu , Nikhil A. Madhusudhana , Joe Nasti

In the realm of digital media, the advent of AI-generated synthetic images has introduced significant challenges in distinguishing between real and fabricated visual content. These images, often indistinguishable from authentic ones, pose a…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Yuyang Wang , Yizhi Hao , Amando Xu Cong

Casually captured Neural Radiance Fields (NeRFs) suffer from artifacts such as floaters or flawed geometry when rendered outside the camera trajectory. Existing evaluation protocols often do not capture these effects, since they usually…

Computer Vision and Pattern Recognition · Computer Science 2023-10-19 Frederik Warburg , Ethan Weber , Matthew Tancik , Aleksander Holynski , Angjoo Kanazawa

Recent progress in generative AI, primarily through diffusion models, presents significant challenges for real-world deepfake detection. The increased realism in image details, diverse content, and widespread accessibility to the general…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Chaitali Bhattacharyya , Hanxiao Wang , Feng Zhang , Sungho Kim , Xiatian Zhu

Artificial Intelligence (AI) tools have become incredibly powerful in generating synthetic images. Of particular concern are generated images that resemble photographs as they aspire to represent real world events. Synthetic photographs may…

Computers and Society · Computer Science 2024-08-14 Melanie Mathys , Marco Willi , Raphael Meier

An experimental study on detecting synthetic face images is presented. We collected a dataset, called FF5, of five fake face image generators, including recent diffusion models. We find that a simple model trained on a specific image…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Nela Petrzelkova , Jan Cech

Nighttime image dehazing remains a challenging low-level vision problem due to the joint presence of haze, glow, non-uniform illumination, color distortion, and sensor noise, which often invalidate assumptions commonly used in daytime…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Mohammad Heydari , Wei Dong , Shahram Shirani , Jun Chen , Han Zhou

Automatic document content processing is affected by artifacts caused by the shape of the paper, non-uniform and diverse color of lighting conditions. Fully-supervised methods on real data are impossible due to the large amount of data…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Sagnik Das , Hassan Ahmed Sial , Ke Ma , Ramon Baldrich , Maria Vanrell , Dimitris Samaras

We introduce FakeParts, a new class of deepfakes characterized by subtle, localized manipulations to specific spatial regions or temporal segments of otherwise authentic videos. Unlike fully synthetic content, these partial manipulations -…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Ziyi Liu , Firas Gabetni , Awais Hussain Sani , Xi Wang , Soobash Daiboo , Gaetan Brison , Gianni Franchi , Vicky Kalogeiton

Face fill-light enhancement (FFE) brightens underexposed faces by adding virtual fill light while keeping the original scene illumination and background unchanged. Most face relighting methods aim to reshape overall lighting, which can…

Computer Vision and Pattern Recognition · Computer Science 2026-02-05 Jue Gong , Zihan Zhou , Jingkai Wang , Xiaohong Liu , Yulun Zhang , Xiaokang Yang

Transparent objects such as windows and bottles made by glass widely exist in the real world. Segmenting transparent objects is challenging because these objects have diverse appearance inherited from the image background, making them had…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Enze Xie , Wenjia Wang , Wenhai Wang , Mingyu Ding , Chunhua Shen , Ping Luo