1 code implementation • 17 Nov 2023 • Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez, Minchul Kim, Christian Rathgeb, Xiaoming Liu, Ivan DeAndres-Tame, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia, Weisong Zhao, Xiangyu Zhu, Zheyu Yan, Xiao-Yu Zhang, Jinlin Wu, Zhen Lei, Suvidha Tripathi, Mahak Kothari, Md Haider Zama, Debayan Deb, Bernardo Biesseck, Pedro Vidal, Roger Granada, Guilherme Fickel, Gustavo Führ, David Menotti, Alexander Unnervik, Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza, Parsa Rahimi, Sébastien Marcel, Ioannis Sarridis, Christos Koutlis, Georgia Baltsou, Symeon Papadopoulos, Christos Diou, Nicolò Di Domenico, Guido Borghi, Lorenzo Pellegrini, Enrique Mas-Candela, Ángela Sánchez-Pérez, Andrea Atzori, Fadi Boutros, Naser Damer, Gianni Fenu, Mirko Marras
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail.
no code implementations • 4 Oct 2023 • Debayan Deb, Suvidha Tripathi, Pranit Puri
We propose a method that offers quality, diversity, control, and realism along with explainable network design, all desirable features to game-design artists in the domain.
no code implementations • 10 Jan 2023 • Debayan Deb, Vishesh Mistry, Rahul Parthe
With the advent of deep learning models, face recognition systems have achieved impressive recognition rates.
no code implementations • 22 Aug 2021 • Inci M. Baytas, Debayan Deb
However, the adversarial training with gradient-based attacks lacks diversity and does not generalize well to natural images and various attacks.
no code implementations • 14 May 2021 • Anil K. Jain, Debayan Deb, Joshua J. Engelsma
Over the past two decades, biometric recognition has exploded into a plethora of different applications around the globe.
no code implementations • 5 Apr 2021 • Debayan Deb, Xiaoming Liu, Anil K. Jain
Proposed UniFAD outperforms prevailing defense methods and their fusion with an overall TDR = 94. 73% @ 0. 2% FDR on a large fake face dataset consisting of 341K bona fide images and 448K attack images of 25 types across all 3 categories.
no code implementations • 28 Nov 2020 • Debayan Deb, Xiaoming Liu, Anil K. Jain
During training, FaceGuard automatically synthesizes challenging and diverse adversarial attacks, enabling a classifier to learn to distinguish them from real faces and a purifier attempts to remove the adversarial perturbations in the image space.
1 code implementation • 7 Oct 2020 • Joshua J. Engelsma, Debayan Deb, Kai Cao, Anjoo Bhatnagar, Prem S. Sudhish, Anil K. Jain
In many of the least developed and developing countries, a multitude of infants continue to suffer and die from vaccine-preventable diseases and malnutrition.
no code implementations • 4 Jun 2020 • Debayan Deb, Anil K. Jain
State-of-the-art spoof detection methods tend to overfit to the spoof types seen during training and fail to generalize to unknown spoof types.
no code implementations • 17 Mar 2020 • Debayan Deb, Divyansh Aggarwal, Anil K. Jain
Given a gallery of face images of missing children, state-of-the-art face recognition systems fall short in identifying a child (probe) recovered at a later age.
no code implementations • 18 Nov 2019 • Debayan Deb, Divyansh Aggarwal, Anil K. Jain
Given a gallery of face images of missing children, state-of-the-art face recognition systems fall short in identifying a child (probe) recovered at a later age.
4 code implementations • 17 Sep 2019 • Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain
In this survey, we review the state of the art algorithms for generating adversarial examples and the countermeasures against adversarial examples, for the three popular data types, i. e., images, graphs and text.
1 code implementation • 14 Aug 2019 • Debayan Deb, Jianbang Zhang, Anil K. Jain
Face recognition systems have been shown to be vulnerable to adversarial examples resulting from adding small perturbations to probe images.
1 code implementation • 1 Apr 2019 • Joshua J. Engelsma, Debayan Deb, Anil K. Jain, Prem S. Sudhish, Anjoo Bhatnager
In developing countries around the world, a multitude of infants continue to suffer and die from vaccine-preventable diseases, and malnutrition.
no code implementations • 16 Jan 2019 • Debayan Deb, Arun Ross, Anil K. Jain, Kwaku Prakah-Asante, K. Venkatesh Prasad
Prevailing user authentication schemes on smartphones rely on explicit user interaction, where a user types in a passcode or presents a biometric cue such as face, fingerprint, or iris.
3 code implementations • CVPR 2019 • Yichun Shi, Debayan Deb, Anil K. Jain
We propose, WarpGAN, a fully automatic network that can generate caricatures given an input face photo.
no code implementations • 2 May 2018 • Elham Tabassi, Tarang Chugh, Debayan Deb, Anil K. Jain
Fingerprint alteration, also referred to as obfuscation presentation attack, is to intentionally tamper or damage the real friction ridge patterns to avoid identification by an AFIS.
1 code implementation • 24 Apr 2018 • Debayan Deb, Susan Wiper, Alexandra Russo, Sixue Gong, Yichun Shi, Cori Tymoszek, Anil Jain
We present a new method of primate face recognition, and evaluate this method on several endangered primates, including golden monkeys, lemurs, and chimpanzees.
no code implementations • 22 Apr 2018 • Debayan Deb, Tarang Chugh, Joshua Engelsma, Kai Cao, Neeta Nain, Jake Kendall, Anil K. Jain
We address the problem of comparing fingerphotos, fingerprint images from a commodity smartphone camera, with the corresponding legacy slap contact-based fingerprint images.
1 code implementation • 10 Nov 2017 • Debayan Deb, Neeta Nain, Anil K. Jain
Face comparison scores are obtained from (i) a state-of-the-art COTS matcher (COTS-A), (ii) an open-source matcher (FaceNet), and (iii) a simple sum fusion of scores obtained from COTS-A and FaceNet matchers.