1 code implementation • 23 Jan 2025 • Abhishek Tandon, Geetanjali Sharma, Gaurav Jaswal, Aditya Nigam, Raghavendra Ramachandra
We propose a trait-specific image generation method that models forehead creases geometrically using B-spline and B\'ezier curves.
no code implementations • 16 Jan 2025 • Haoyu Zhang, Raghavendra Ramachandra, Kiran Raja, Christoph Busch
The problem of generalization is further pronounced when the detection has to be made on a single suspected image.
no code implementations • 14 Jan 2025 • Wassim Kabbani, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
Face image quality assessment (FIQA) algorithms are being integrated into online identity management applications.
no code implementations • 13 Jan 2025 • Wassim Kabbani, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
The sclera region is agnostic to demographic variations and skin colour for assessing the quality of a face image.
no code implementations • 13 Jan 2025 • Wassim Kabbani, Tristan Le Pessot, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
We formalize the detection model as a face image quality assessment (FIQA) algorithm and provide a careful inspection of the effect of radial distortion on FRS performance.
no code implementations • 13 Jan 2025 • Wassim Kabbani, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
A face image is a mandatory part of ID and travel documents.
2 code implementations • 6 Jan 2025 • Guray Ozgur, Eduarda Caldeira, Tahar Chettaoui, Fadi Boutros, Raghavendra Ramachandra, Naser Damer
Although face recognition systems have seen a massive performance enhancement in recent years, they are still targeted by threats such as presentation attacks, leading to the need for generalizable presentation attack detection (PAD) algorithms.
no code implementations • 14 Nov 2024 • Ayush Agarwal, Raghavendra Ramachandra, Sushma Venkatesh, S. R. Mahadeva Prasanna
In the domain of Extended Reality (XR), particularly Virtual Reality (VR), extensive research has been devoted to harnessing this transformative technology in various real-world applications.
no code implementations • 13 Nov 2024 • Geetanjali Sharma, Abhishek Tandon, Gaurav Jaswal, Aditya Nigam, Raghavendra Ramachandra
Furthermore, we examined the generalization capabilities of these systems across different iris colors and devices, finding that while training on diverse datasets enhances recognition performance, the degree of improvement is contingent on the specific model and device used.
no code implementations • 10 Oct 2024 • Aravinda Reddy PN, Raghavendra Ramachandra, Sushma Venkatesh, Krothapalli Sreenivasa Rao, Pabitra Mitra, Rakesh Krishna
The obtained results indicate the highest attack potential of the proposed \textit{MorCode} when compared with five state-of-the-art morphing generation methods on both digital and print scan data.
no code implementations • 27 Sep 2024 • Hailin Li, Raghavendra Ramachandra, Mohamed Ragab, Soumik Mondal, Yong Kiam Tan, Khin Mi Mi Aung
Smartphone-based contactless fingerphoto authentication has become a reliable alternative to traditional contact-based fingerprint biometric systems owing to rapid advances in smartphone camera technology.
no code implementations • 9 Sep 2024 • Haoyu Zhang, Raghavendra Ramachandra, Kiran Raja, Christoph Busch
Face morphing attack detection (MAD) algorithms have become essential to overcome the vulnerability of face recognition systems.
1 code implementation • 28 Aug 2024 • Abhishek Tandon, Geetanjali Sharma, Gaurav Jaswal, Aditya Nigam, Raghavendra Ramachandra
In addition, we assess the utility of synthetically generated forehead-crease images using a forehead-crease verification system (FHCVS).
no code implementations • 19 Jun 2024 • Aravinda Reddy PN, Raghavendra Ramachandra, Krothapalli Sreenivasa Rao, Pabitra Mitra, Vinod Rathod
In this paper, we introduce the Straight-through Gumbel-Softmax (STGS) framework, offering a comprehensive approach to search multimodal fusion model architectures.
no code implementations • 2 May 2024 • Praveen Kumar Chandaliya, Kiran Raja, Raghavendra Ramachandra, Zahid Akhtar, Christoph Busch
Numerous studies have shown that existing Face Recognition Systems (FRS), including commercial ones, often exhibit biases toward certain ethnicities due to under-represented data.
no code implementations • 24 Apr 2024 • Jag Mohan Singh, Raghavendra Ramachandra
The proposed method generates 388 face-morphing point clouds from 200 bona fide subjects.
no code implementations • 19 Apr 2024 • Aravinda Reddy PN, Raghavendra Ramachandra, Krothapalli Sreenivasa Rao, Pabitra Mitra
Face-morphing attacks are a growing concern for biometric researchers, as they can be used to fool face recognition systems (FRS).
no code implementations • 19 Apr 2024 • Raghavendra Ramachandra, Narayan Vetrekar, Sushma Venkatesh, Savita Nageshker, Jag Mohan Singh, R. S. Gad
In this work, we propose a novel Presentation Attack Detection (PAD) algorithm based on 3D point clouds captured using the frontal camera of a smartphone to detect presentation attacks.
1 code implementation • 15 Apr 2024 • Zheng Chen, Zongwei Wu, Eduard Zamfir, Kai Zhang, Yulun Zhang, Radu Timofte, Xiaokang Yang, Hongyuan Yu, Cheng Wan, Yuxin Hong, Zhijuan Huang, Yajun Zou, Yuan Huang, Jiamin Lin, Bingnan Han, Xianyu Guan, Yongsheng Yu, Daoan Zhang, Xuanwu Yin, Kunlong Zuo, Jinhua Hao, Kai Zhao, Kun Yuan, Ming Sun, Chao Zhou, Hongyu An, Xinfeng Zhang, Zhiyuan Song, Ziyue Dong, Qing Zhao, Xiaogang Xu, Pengxu Wei, Zhi-chao Dou, Gui-ling Wang, Chih-Chung Hsu, Chia-Ming Lee, Yi-Shiuan Chou, Cansu Korkmaz, A. Murat Tekalp, Yubin Wei, Xiaole Yan, Binren Li, Haonan Chen, Siqi Zhang, Sihan Chen, Amogh Joshi, Nikhil Akalwadi, Sampada Malagi, Palani Yashaswini, Chaitra Desai, Ramesh Ashok Tabib, Ujwala Patil, Uma Mudenagudi, Anjali Sarvaiya, Pooja Choksy, Jagrit Joshi, Shubh Kawa, Kishor Upla, Sushrut Patwardhan, Raghavendra Ramachandra, Sadat Hossain, Geongi Park, S. M. Nadim Uddin, Hao Xu, Yanhui Guo, Aman Urumbekov, Xingzhuo Yan, Wei Hao, Minghan Fu, Isaac Orais, Samuel Smith, Ying Liu, Wangwang Jia, Qisheng Xu, Kele Xu, Weijun Yuan, Zhan Li, Wenqin Kuang, Ruijin Guan, Ruting Deng, Zhao Zhang, Bo wang, Suiyi Zhao, Yan Luo, Yanyan Wei, Asif Hussain Khan, Christian Micheloni, Niki Martinel
This paper reviews the NTIRE 2024 challenge on image super-resolution ($\times$4), highlighting the solutions proposed and the outcomes obtained.
no code implementations • 24 Mar 2024 • Geetanjali Sharma, Gaurav Jaswal, Aditya Nigam, Raghavendra Ramachandra
The results demonstrate the superior performance of FH-SSTNet for forehead-based user verification, confirming its effectiveness in identity authentication.
1 code implementation • CVPR 2024 • Revoti Prasad Bora, Philipp Terhörst, Raymond Veldhuis, Raghavendra Ramachandra, Kiran Raja
Explanations are then extracted for a black-box model and a given IE using the surrogate model.
no code implementations • 20 Nov 2023 • Narayan Vetrekar, Raghavendra Ramachandra, Sushma Venkatesh, Jyoti D. Pawar, R. S. Gad
We present PAD based on multispectral images constructed for eight different presentation artifacts resulted from three different artifact species.
2 code implementations • 9 Nov 2023 • Meiling Fang, Marco Huber, Julian Fierrez, Raghavendra Ramachandra, Naser Damer, Alhasan Alkhaddour, Maksim Kasantcev, Vasiliy Pryadchenko, Ziyuan Yang, Huijie Huangfu, Yingyu Chen, Yi Zhang, Yuchen Pan, Junjun Jiang, Xianming Liu, Xianyun Sun, Caiyong Wang, Xingyu Liu, Zhaohua Chang, Guangzhe Zhao, Juan Tapia, Lazaro Gonzalez-Soler, Carlos Aravena, Daniel Schulz
This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 International Joint Conference on Biometrics (IJCB 2023).
no code implementations • 25 Oct 2023 • Raghavendra Ramachandra, Sushma Venkatesh
The proposed VeinAtnNet was trained on the newly constructed fingervein dataset with 300 unique fingervein patterns that were captured in multiple sessions to obtain 92 samples per unique fingervein.
1 code implementation • 19 Oct 2023 • Aravinda Reddy PN, K. Sreenivasa Rao, Raghavendra Ramachandra, Pabitra Mitra
We present a novel face swapping method using the progressively growing structure of a pre-trained StyleGAN.
no code implementations • 24 Sep 2023 • Raghavendra Ramachandra, Jag Mohan Singh, Sushma Venkatesh
In this paper, we present an acoustic echo-based face Presentation Attack Detection (PAD) on a smartphone in which the PAs are detected based on the reflection profiles of the transmitted signal.
no code implementations • 4 Jul 2023 • Hailin Li, Raghavendra Ramachandra
The rapid evolution of high-end smartphones with advanced high-resolution cameras has resulted in contactless capture of fingerprint biometrics that are more reliable and suitable for verification.
no code implementations • 27 May 2023 • Hailin Li, Raghavendra Ramachandra
The vulnerabilities of fingerprint authentication systems have raised security concerns when adapting them to highly secure access-control applications.
no code implementations • 2 May 2023 • Raghavendra Ramachandra, Sushma Venkatesh, Guoqiang Li, Kiran Raja
Face Recognition System (FRS) are shown to be vulnerable to morphed images of newborns.
no code implementations • 7 Apr 2023 • Raghavendra Ramachandra, Sushma Venkatesh, Naser Damer, Narayan Vetrekar, Rajendra Gad
The D-MAD methods are based on using two facial images that are captured from the ePassport (also called the reference image) and the trusted device (for example, Automatic Border Control (ABC) gates) to detect whether the face image presented in ePassport is morphed.
no code implementations • 3 Apr 2023 • Xinwei Liu, Kiran Raja, Renfang Wang, Hong Qiu, Hucheng Wu, Dechao Sun, Qiguang Zheng, Nian Liu, Xiaoxia Wang, Gehang Huang, Raghavendra Ramachandra, Christoph Busch
Further, existing databases for latent fingerprint recognition do not have a large number of unique subjects/fingerprint instances or do not provide ground truth/reference fingerprint images to conduct a cross-comparison against the latent.
no code implementations • 24 Mar 2023 • Raghavendra Ramachandra, Sushma Venkatesh, Gaurav Jaswal, Guoqiang Li
We present a systematic study on benchmarking the vulnerability of Face Recognition Systems (FRS) to lookalike and identical twin morphing images.
no code implementations • CVPR 2023 • Haoqian Wu, Keyu Chen, Haozhe Liu, Mingchen Zhuge, Bing Li, Ruizhi Qiao, Xiujun Shu, Bei Gan, Liangsheng Xu, Bo Ren, Mengmeng Xu, Wentian Zhang, Raghavendra Ramachandra, Chia-Wen Lin, Bernard Ghanem
Temporal video segmentation is the get-to-go automatic video analysis, which decomposes a long-form video into smaller components for the following-up understanding tasks.
no code implementations • 9 Dec 2022 • Raghavendra Ramachandra, Hailin Li
Fingerphoto images captured using a smartphone are successfully used to verify the individuals that have enabled several applications.
no code implementations • 22 Nov 2022 • Dhruv Patel, Abhinav Jain, Simran Bawkar, Manav Khorasiya, Kalpesh Prajapati, Kishor Upla, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
We introduce a new triplet-based adversarial loss function that exploits the information provided in the LR image by using it as a negative sample.
1 code implementation • 20 Nov 2022 • Jag Mohan Singh, Raghavendra Ramachandra
Given the face images corresponding to two unique data subjects, the proposed CFIA method will independently generate the segmented facial attributes, then blend them using transparent masks to generate the CFIA samples.
no code implementations • 30 Sep 2022 • Jag Mohan Singh, Raghavendra Ramachandra
Among these attacks, face morphing attacks are highly potential in deceiving automatic FRS and human observers and indicate a severe security threat, especially in the border control scenario.
no code implementations • 25 Sep 2022 • Wentian Zhang, Haozhe Liu, Feng Liu, Raghavendra Ramachandra
For reconstruction performance, our method achieves the best performance with 0. 834 mIOU and 0. 937 PA. By comparing with the recognition performance on surface 2D fingerprints, the effectiveness of our proposed method on high quality subsurface fingerprint reconstruction is further proved.
no code implementations • 17 Aug 2022 • Marcel Grimmer, Haoyu Zhang, Raghavendra Ramachandra, Kiran Raja, Christoph Busch
The vast progress in synthetic image synthesis enables the generation of facial images in high resolution and photorealism.
1 code implementation • 15 Aug 2022 • Marco Huber, Fadi Boutros, Anh Thi Luu, Kiran Raja, Raghavendra Ramachandra, Naser Damer, Pedro C. Neto, Tiago Gonçalves, Ana F. Sequeira, Jaime S. Cardoso, João Tremoço, Miguel Lourenço, Sergio Serra, Eduardo Cermeño, Marija Ivanovska, Borut Batagelj, Andrej Kronovšek, Peter Peer, Vitomir Štruc
The competition attracted a total of 12 participating teams, both from academia and industry and present in 11 different countries.
1 code implementation • 1 Jul 2022 • Sauradip Nag, Nisarg Shah, Anran Qi, Raghavendra Ramachandra
Unlike previous methods, we model the depth estimation of the unobserved frame as a view-synthesis problem, which treats the depth estimate of the unseen video frame as an auxiliary task while synthesizing back the views using learned pose.
no code implementations • 24 Feb 2022 • Sankini Rancha Godage, Frøy Løvåsdal, Sushma Venkatesh, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
One prevalent misconception is that an examiner's or observer's capacity for facial morph detection depends on their subject expertise, experience, and familiarity with the issue and that no works have reported the specific results of observers who regularly verify identity (ID) documents for their jobs.
1 code implementation • 10 Jan 2022 • Jag Mohan Singh, Raghavendra Ramachandra
To this extent, we introduced a novel approach based on blending 3D face point clouds corresponding to contributory data subjects.
no code implementations • 7 Dec 2021 • Marcel Grimmer, Haoyu Zhang, Raghavendra Ramachandra, Kiran Raja, Christoph Busch
Mated samples are generated by manipulating latent vectors, and more precisely, we exploit Principal Component Analysis (PCA) to define semantically meaningful directions in the latent space and control the similarity between the original and the mated samples using a pre-trained face recognition system.
no code implementations • 23 Nov 2021 • Raghavendra Ramachandra, Kiran Raja, Christoph Busch
In this paper, we study and present a comprehensive analysis of algorithmic fairness of the existing Single image-based Morph Attack Detection (S-MAD) algorithms.
2 code implementations • 22 Nov 2021 • Wentian Zhang, Haozhe Liu, Feng Liu, Raghavendra Ramachandra, Christoph Busch
The proposed method, first introduces task specific features from other face related task, then, we design a Cross-Modal Adapter using a Graph Attention Network (GAT) to re-map such features to adapt to PAD task.
no code implementations • 1 Nov 2021 • Gaurav Jaswal, Aman Verma, Sumantra Dutta Roy, Raghavendra Ramachandra
To alleviate these shortcomings, this paper proposes DFCANet: Dense Feature Calibration and Attention Guided Network which calibrates the locally spread iris patterns with the globally located ones.
Cross-Domain Iris Presentation Attack Detection
Incremental Learning
+1
1 code implementation • 9 Sep 2021 • Zhe Kong, Wentian Zhang, Feng Liu, Wenhan Luo, Haozhe Liu, Linlin Shen, Raghavendra Ramachandra
Even though there are numerous Presentation Attack Detection (PAD) techniques based on both deep learning and hand-crafted features, the generalization of PAD for unknown PAI is still a challenging problem.
no code implementations • 9 Sep 2021 • Hareesh Mandalapu, Aravinda Reddy P N, Raghavendra Ramachandra, K Sreenivasa Rao, Pabitra Mitra, S R Mahadeva Prasanna, Christoph Busch
This new dataset contains 103 subjects captured in three different sessions considering the different real-world scenarios.
no code implementations • 20 Aug 2021 • Naser Damer, Kiran Raja, Marius Süßmilch, Sushma Venkatesh, Fadi Boutros, Meiling Fang, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper
Face morphing attacks aim at creating face images that are verifiable to be the face of multiple identities, which can lead to building faulty identity links in operations like border checks.
no code implementations • 29 Jun 2021 • Fadi Boutros, Naser Damer, Jan Niklas Kolf, Kiran Raja, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper, Pengcheng Fang, Chao Zhang, Fei Wang, David Montero, Naiara Aginako, Basilio Sierra, Marcos Nieto, Mustafa Ekrem Erakin, Ugur Demir, Hazim Kemal, Ekenel, Asaki Kataoka, Kohei Ichikawa, Shizuma Kubo, Jie Zhang, Mingjie He, Dan Han, Shiguang Shan, Klemen Grm, Vitomir Štruc, Sachith Seneviratne, Nuran Kasthuriarachchi, Sanka Rasnayaka, Pedro C. Neto, Ana F. Sequeira, Joao Ribeiro Pinto, Mohsen Saffari, Jaime S. Cardoso
These teams successfully submitted 18 valid solutions.
2 code implementations • 17 May 2021 • Andrey Ignatov, Cheng-Ming Chiang, Hsien-Kai Kuo, Anastasia Sycheva, Radu Timofte, Min-Hung Chen, Man-Yu Lee, Yu-Syuan Xu, Yu Tseng, Shusong Xu, Jin Guo, Chao-Hung Chen, Ming-Chun Hsyu, Wen-Chia Tsai, Chao-Wei Chen, Grigory Malivenko, Minsu Kwon, Myungje Lee, Jaeyoon Yoo, Changbeom Kang, Shinjo Wang, Zheng Shaolong, Hao Dejun, Xie Fen, Feng Zhuang, Yipeng Ma, Jingyang Peng, Tao Wang, Fenglong Song, Chih-Chung Hsu, Kwan-Lin Chen, Mei-Hsuang Wu, Vishal Chudasama, Kalpesh Prajapati, Heena Patel, Anjali Sarvaiya, Kishor Upla, Kiran Raja, Raghavendra Ramachandra, Christoph Busch, Etienne de Stoutz
As the quality of mobile cameras starts to play a crucial role in modern smartphones, more and more attention is now being paid to ISP algorithms used to improve various perceptual aspects of mobile photos.
no code implementations • 6 Apr 2021 • Haoyu Zhang, Marcel Grimmer, Raghavendra Ramachandra, Kiran Raja, Christoph Busch
Face verification has come into increasing focus in various applications including the European Entry/Exit System, which integrates face recognition mechanisms.
no code implementations • 3 Nov 2020 • Sushma Venkatesh, Raghavendra Ramachandra, Kiran Raja, Christoph Busch
The vulnerability of Face Recognition System (FRS) to various kind of attacks (both direct and in-direct attacks) and face morphing attacks has received a great interest from the biometric community.
no code implementations • 20 Oct 2020 • Fadi Boutros, Naser Damer, Kiran Raja, Raghavendra Ramachandra, Florian Kirchbuchner, Arjan Kuijper
Motivated by the performance of iris recognition, we also propose the continuous authentication of users in a non-collaborative capture setting in HMD.
no code implementations • 3 Sep 2020 • Haoyu Zhang, Sushma Venkatesh, Raghavendra Ramachandra, Kiran Raja, Naser Damer, Christoph Busch
Extensive experiments are carried out to assess the FRS's vulnerability against the proposed morphed face generation technique on three types of data such as digital images, re-digitized (printed and scanned) images, and compressed images after re-digitization from newly generated MIPGAN Face Morph Dataset.
no code implementations • 22 Jul 2020 • Fatemeh Vakhshiteh, Ahmad Nickabadi, Raghavendra Ramachandra
Face recognition (FR) systems have demonstrated outstanding verification performance, suggesting suitability for real-world applications ranging from photo tagging in social media to automated border control (ABC).
no code implementations • 7 Jul 2020 • Sushma Venkatesh, Haoyu Zhang, Raghavendra Ramachandra, Kiran Raja, Naser Damer, Christoph Busch
\textit{(i) Can GAN generated morphs threaten Face Recognition Systems (FRS) equally as Landmark based morphs?}
no code implementations • 6 Jul 2020 • Sushma Venkatesh, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
To this extent, we have introduced a new morphed face dataset with ageing derived from the publicly available MORPH II face dataset, which we refer to as MorphAge dataset.
no code implementations • 11 Jun 2020 • Kiran Raja, Matteo Ferrara, Annalisa Franco, Luuk Spreeuwers, Illias Batskos, Florens de Wit Marta Gomez-Barrero, Ulrich Scherhag, Daniel Fischer, Sushma Venkatesh, Jag Mohan Singh, Guoqiang Li, Loïc Bergeron, Sergey Isadskiy, Raghavendra Ramachandra, Christian Rathgeb, Dinusha Frings, Uwe Seidel, Fons Knopjes, Raymond Veldhuis, Davide Maltoni, Christoph Busch
Further, we present a new online evaluation platform to test algorithms on sequestered data.
no code implementations • 17 May 2020 • Jag Mohan Singh, Ahmed Madhun, Guoqiang Li, Raghavendra Ramachandra
Fingerprint recognition systems are widely deployed in various real-life applications as they have achieved high accuracy.
no code implementations • 5 Dec 2019 • Raghavendra Ramachandra, Martin Stokkenes, Amir Mohammadi, Sushma Venkatesh, Kiran Raja, Pankaj Wasnik, Eric Poiret, Sébastien Marcel, Christoph Busch
One of the unique features of this dataset is that it is collected in four different geographic locations representing a diverse population and ethnicity.
no code implementations • 3 Dec 2019 • Jag Mohan Singh, Sushma Venkatesh, Kiran B. Raja, Raghavendra Ramachandra, Christoph Busch
We establish the superiority of the proposed approach by benchmarking it with classical textural feature-descriptor applied directly on finger-vein images.
no code implementations • 3 Dec 2019 • Jag Mohan Singh, Raghavendra Ramachandra, Kiran B. Raja, Christoph Busch
Face recognition is widely employed in Automated Border Control (ABC) gates, which verify the face image on passport or electronic Machine Readable Travel Document (eMTRD) against the captured image to confirm the identity of the passport holder.