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Existing approaches to improve the performances of convolutional neural networks by optimizing the local architectures or deepening the networks tend to increase the size of models significantly. In order to deploy and apply the neural…

Computer Vision and Pattern Recognition · Computer Science 2020-01-22 Hui Zhu , Zhulin An , Kaiqiang Xu , Xiaolong Hu , Yongjun Xu

One of the open issues in fingerprint verification is the lack of robustness against image-quality degradation. Poor-quality images result in spurious and missing features, thus degrading the performance of the overall system. Therefore, it…

Computer Vision and Pattern Recognition · Computer Science 2021-11-16 Fernando Alonso-Fernandez , Julian Fierrez , Javier Ortega-Garcia , Joaquin Gonzalez-Rodriguez , Hartwig Fronthaler , Klaus Kollreider , Josef Bigun

Visual saliency detection aims at identifying the most visually distinctive parts in an image, and serves as a pre-processing step for a variety of computer vision and image processing tasks. To this end, the saliency detection procedure…

Computer Vision and Pattern Recognition · Computer Science 2017-02-27 Xuanyang Xi , Yongkang Luo , Fengfu Li , Peng Wang , Hong Qiao

We consider the problem of learning deep generative models from data. We formulate a method that generates an independent sample via a single feedforward pass through a multilayer perceptron, as in the recently proposed generative…

Machine Learning · Computer Science 2015-02-11 Yujia Li , Kevin Swersky , Richard Zemel

This paper presents a novel convolutional layer, called perturbed convolution (PConv), which focuses on achieving two goals simultaneously: improving the generative adversarial network (GAN) performance and alleviating the memorization…

Computer Vision and Pattern Recognition · Computer Science 2021-12-23 Seung Park , Yoon-Jae Yeo , Yong-Goo Shin

Image inpainting aims to restore the missing regions of corrupted images and make the recovery result identical to the originally complete image, which is different from the common generative task emphasizing the naturalness or realism of…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Qing Guo , Xiaoguang Li , Felix Juefei-Xu , Hongkai Yu , Yang Liu , Song wang

State-of-the-art (SOTA) Generative Models (GMs) can synthesize photo-realistic images that are hard for humans to distinguish from genuine photos. Identifying and understanding manipulated media are crucial to mitigate the social concerns…

Computer Vision and Pattern Recognition · Computer Science 2023-08-01 Vishal Asnani , Xi Yin , Tal Hassner , Xiaoming Liu

Recent years have witnessed the great advance of deep learning in a variety of vision tasks. Many state-of-the-art deep neural networks suffer from large size and high complexity, which makes it difficult to deploy in resource-limited…

Computer Vision and Pattern Recognition · Computer Science 2019-05-29 Zhengguang Zhou , Wengang Zhou , Xutao Lv , Xuan Huang , Xiaoyu Wang , Houqiang Li

Advances in Artificial Intelligence and Image Processing are changing the way people interacts with digital images and video. Widespread mobile apps like FACEAPP make use of the most advanced Generative Adversarial Networks (GAN) to produce…

Computer Vision and Pattern Recognition · Computer Science 2020-09-14 Luca Guarnera , Oliver Giudice , Sebastiano Battiato

The fingerprint classification problem is to sort fingerprints into pre-determined groups, such as arch, loop, and whorl. It was asserted in the literature that minutiae points, which are commonly used for fingerprint matching, are not…

Machine Learning · Statistics 2017-11-28 Noah Giansiracusa , Robert Giansiracusa , Chul Moon

Deep convolutional networks have become a popular tool for image generation and restoration. Generally, their excellent performance is imputed to their ability to learn realistic image priors from a large number of example images. In this…

Computer Vision and Pattern Recognition · Computer Science 2020-05-19 Dmitry Ulyanov , Andrea Vedaldi , Victor Lempitsky

Image classification is an essential task in computer vision, which aims to categorise a set of images into different groups based on some visual criteria. Existing methods, such as convolutional neural networks, have been successfully…

Neural and Evolutionary Computing · Computer Science 2019-10-01 Benjamin Patrick Evans , Harith Al-Sahaf , Bing Xue , Mengjie Zhang

Face deidentification is an active topic amongst privacy and security researchers. Early deidentification methods relying on image blurring or pixelization were replaced in recent years with techniques based on formal anonymity models that…

Computer Vision and Pattern Recognition · Computer Science 2017-08-01 Blaž Meden , Refik Can Mallı , Sebastjan Fabijan , Hazım Kemal Ekenel , Vitomir Štruc , Peter Peer

In this paper, we rethink the low-light image enhancement task and propose a physically explainable and generative diffusion model for low-light image enhancement, termed as Diff-Retinex. We aim to integrate the advantages of the physical…

Computer Vision and Pattern Recognition · Computer Science 2023-08-28 Xunpeng Yi , Han Xu , Hao Zhang , Linfeng Tang , Jiayi Ma

The effectiveness of fingerprint-based authentication systems on good quality fingerprints is established long back. However, the performance of standard fingerprint matching systems on noisy and poor quality fingerprints is far from…

Computer Vision and Pattern Recognition · Computer Science 2021-07-06 Indu Joshi , Ayush Utkarsh , Riya Kothari , Vinod K Kurmi , Antitza Dantcheva , Sumantra Dutta Roy , Prem Kumar Kalra

Computer vision often uses highly accurate Convolutional Neural Networks (CNNs), but these deep learning models are associated with ever-increasing energy and computation requirements. Producing more energy-efficient CNNs often requires…

The selection of features is an essential data preprocessing stage in data mining. The core principle of feature selection seems to be to pick a subset of possible features by excluding features with almost no predictive information as well…

Machine Learning · Computer Science 2020-08-11 Mehrdad Rostami , Kamal Berahmand , Saman Forouzandeh

Deepfakes represent one of the toughest challenges in the world of Cybersecurity and Digital Forensics, especially considering the high-quality results obtained with recent generative AI-based solutions. Almost all generative models leave…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Orazio Pontorno , Luca Guarnera , Sebastiano Battiato

Biometric verification systems are deployed in various security-based access-control applications that require user-friendly and reliable person verification. Among the different biometric characteristics, fingervein biometrics have been…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 Raghavendra Ramachandra , Sushma Venkatesh

Image denoising aims to remove noise while preserving structural details and perceptual realism, yet distortion-driven methods often produce over-smoothed reconstructions, especially under strong noise and distribution shift. This paper…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Nam Nguyen , Thinh Nguyen , Bella Bose
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