2021 IEEE International Joint Conference on Biometrics (IJCB)最新文献_第8页

Simultaneous Face Hallucination and Translation for Thermal to Visible Face Verification using Axial-GAN 基于轴向氮化镓的同步人脸幻觉和热到可见人脸的转换验证

2021 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2021-04-13 DOI: 10.1109/IJCB52358.2021.9484353

Rakhil Immidisetti, Shuowen Hu, Vishal M. Patel

引用次数: 13

FedFace: Collaborative Learning of Face Recognition Model FedFace:人脸识别模型的协同学习

2021 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2021-04-07 DOI: 10.1109/IJCB52358.2021.9484386

Divyansh Aggarwal, Jiayu Zhou, Anil K. Jain

引用次数: 28

A Unified Model for Fingerprint Authentication and Presentation Attack Detection 指纹认证与表示攻击检测的统一模型

2021 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2021-04-07 DOI: 10.1109/IJCB52358.2021.9484382

Additya Popli, Saraansh Tandon, Joshua J. Engelsma, N. Onoe, Atsushi Okubo, A. Namboodiri

{"title":"A Unified Model for Fingerprint Authentication and Presentation Attack Detection","authors":"Additya Popli, Saraansh Tandon, Joshua J. Engelsma, N. Onoe, Atsushi Okubo, A. Namboodiri","doi":"10.1109/IJCB52358.2021.9484382","DOIUrl":"https://doi.org/10.1109/IJCB52358.2021.9484382","url":null,"abstract":"Typical fingerprint recognition systems are comprised of a spoof detection module and a subsequent recognition module, running one after the other. In this paper, we reformulate the workings of a typical fingerprint recognition system. In particular, we posit that both spoof detection and fingerprint recognition are correlated tasks. Therefore, rather than performing the two tasks separately, we propose a joint model for spoof detection and matching1 to simultaneously perform both tasks without compromising the accuracy of either task. We demonstrate the capability of our joint model to obtain an authentication accuracy (1:1 matching) of TAR = 100% @ FAR = 0.1% on the FVC 2006 DB2A dataset while achieving a spoof detection ACE of 1.44% on the LiveDet 2015 dataset, both maintaining the performance of stand-alone methods. In practice, this reduces the time and memory requirements of the fingerprint recognition system by 50% and 40%, respectively; a significant advantage for recognition systems running on resource-constrained devices and communication channels.","PeriodicalId":175984,"journal":{"name":"2021 IEEE International Joint Conference on Biometrics (IJCB)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127244728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing 视觉变压器对零射人脸抗欺骗的有效性研究

2021 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2020-11-16 DOI: 10.1109/IJCB52358.2021.9484333

Anjith George, S. Marcel

引用次数: 55

SADet: Learning An Efficient and Accurate Pedestrian Detector 学习高效准确的行人检测器

2021 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2020-07-26 DOI: 10.1109/IJCB52358.2021.9484371

Chubin Zhuang, Zongzhao Li, Zhen Lei, S. Li

{"title":"SADet: Learning An Efficient and Accurate Pedestrian Detector","authors":"Chubin Zhuang, Zongzhao Li, Zhen Lei, S. Li","doi":"10.1109/IJCB52358.2021.9484371","DOIUrl":"https://doi.org/10.1109/IJCB52358.2021.9484371","url":null,"abstract":"Although the anchor-based detectors have taken a big step forward in pedestrian detection, the overall performance of algorithm still needs further improvement for practical applications, e.g., a good trade-off between the accuracy and efficiency. To this end, this paper proposes a series of systematic optimization strategies for the detection pipeline of one-stage detector, forming a single shot anchor-based detector (SADet) for efficient and accurate pedestrian detection, which includes three main improvements. Firstly, we optimize the sample generation process by assigning soft labels to the outlier samples to generate semi-positive samples with continuous tag value between 0 and 1. Secondly, a novel Center-IoU loss is applied as a new regression loss for bounding box regression, which not only retains the good characteristics of IoU loss, but also solves some defects of it. Thirdly, we also design Cosine-NMS for the post-processing of predicted bounding boxes, and further propose adaptive anchor matching to enable the model to adaptively match the anchor boxes to full or visible bounding boxes according to the degree of occlusion. Though structurally simple, it presents state-of-the-art result and real-time speed of 20 FPS for VGA-resolution images (640×480) tested on one GeForce GTX 1080Ti GPU on challenging pedestrian detection benchmarks, i.e., CityPersons, Caltech, and human detection benchmark CrowdHuman, leading to a new attractive pedestrian detector.","PeriodicalId":175984,"journal":{"name":"2021 IEEE International Joint Conference on Biometrics (IJCB)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122920668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

2021 International Joint Conference on Biometrics (IJCB 2021) - Event schedule [Table of Contents] 2021国际生物识别联合会议(IJCB 2021) -会议时间表[目录]

2021 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 1900-01-01 DOI: 10.1109/ijcb52358.2021.9521653

引用次数: 0