no code implementations • 24 Nov 2024 • Anuja Vats, Ivar Farup, Marius Pedersen, Kiran Raja
The importance of quantifying uncertainty in deep networks has become paramount for reliable real-world applications.
no code implementations • 25 Oct 2024 • Lakshmi Srinivas Panchananam, Praveen Kumar Chandaliya, Kishor Upla, Kiran Raja
With such consideration, an effective automatic classification of these abnormalities from a video capsule endoscopy (VCE) frame is crucial for improvement in diagnostic workflows.
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.
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.
3 code implementations • 22 Apr 2024 • Xiaoning Liu, Zongwei Wu, Ao Li, Florin-Alexandru Vasluianu, Yulun Zhang, Shuhang Gu, Le Zhang, Ce Zhu, Radu Timofte, Zhi Jin, Hongjun Wu, Chenxi Wang, Haitao Ling, Yuanhao Cai, Hao Bian, Yuxin Zheng, Jing Lin, Alan Yuille, Ben Shao, Jin Guo, Tianli Liu, Mohao Wu, Yixu Feng, Shuo Hou, Haotian Lin, Yu Zhu, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang, Qingsen Yan, Wenbin Zou, Weipeng Yang, Yunxiang Li, Qiaomu Wei, Tian Ye, Sixiang Chen, Zhao Zhang, Suiyi Zhao, Bo wang, Yan Luo, Zhichao Zuo, Mingshen Wang, Junhu Wang, Yanyan Wei, Xiaopeng Sun, Yu Gao, Jiancheng Huang, Hongming Chen, Xiang Chen, Hui Tang, Yuanbin Chen, Yuanbo Zhou, Xinwei Dai, Xintao Qiu, Wei Deng, Qinquan Gao, Tong Tong, Mingjia Li, Jin Hu, Xinyu He, Xiaojie Guo, sabarinathan, K Uma, A Sasithradevi, B Sathya Bama, S. Mohamed Mansoor Roomi, V. Srivatsav, Jinjuan Wang, Long Sun, Qiuying Chen, Jiahong Shao, Yizhi Zhang, Marcos V. Conde, Daniel Feijoo, Juan C. Benito, Alvaro García, Jaeho Lee, Seongwan Kim, Sharif S M A, Nodirkhuja Khujaev, Roman Tsoy, Ali Murtaza, Uswah Khairuddin, Ahmad 'Athif Mohd Faudzi, Sampada Malagi, Amogh Joshi, Nikhil Akalwadi, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudenagudi, Wenyi Lian, Wenjing Lian, Jagadeesh Kalyanshetti, Vijayalaxmi Ashok Aralikatti, Palani Yashaswini, Nitish Upasi, Dikshit Hegde, Ujwala Patil, Sujata C, Xingzhuo Yan, Wei Hao, Minghan Fu, Pooja Choksy, Anjali Sarvaiya, Kishor Upla, Kiran Raja, Hailong Yan, Yunkai Zhang, Baiang Li, Jingyi Zhang, Huan Zheng
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.
2 code implementations • 18 Mar 2024 • Ahmad Hassanpour, Fatemeh Jamalbafrani, Bian Yang, Kiran Raja, Raymond Veldhuis, Julian Fierrez
We further improve the StyleGAN output to find the optimal code in the latent space using a new optimization for GAN inversion technique.
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.
1 code implementation • 22 Dec 2023 • Wassim Kabbani, Christoph Busch, Kiran Raja
Face image quality assessment (FIQA) is crucial for obtaining good face recognition performance.
no code implementations • 2 Nov 2023 • Anuja Vats, David Völgyes, Martijn Vermeer, Marius Pedersen, Kiran Raja, Daniele S. M. Fantin, Jacob Alexander Hay
We test the effectiveness of our approach by evaluating building segmentation performance on test datasets with varying label fractions.
no code implementations • 29 May 2023 • Roman Kessler, Kiran Raja, Juan Tapia, Christoph Busch
The results endorse the advantages of face embeddings in more effective image pre-selection for face morphing and accurate detection of morphed face images.
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 • 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.
1 code implementation • 26 Feb 2023 • Ying Xu, Kiran Raja, Luisa Verdoliva, Marius Pedersen
We obtain 98. 48% BOSC accuracy on the FF++ dataset and 90. 87% BOSC accuracy on the CelebDF dataset suggesting a promising direction for generalization of DeepFake detection.
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.
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.
4 code implementations • 11 Aug 2022 • Ying Xu, Philipp Terhörst, Kiran Raja, Marius Pedersen
In this work, we investigate factors causing biased detection in public Deepfake datasets by (a) creating large-scale demographic and non-demographic attribute annotations with 47 different attributes for five popular Deepfake datasets and (b) comprehensively analysing attributes resulting in AI-bias of three state-of-the-art Deepfake detection backbone models on these datasets.
no code implementations • 23 Mar 2022 • Philipp Terhörst, Florian Bierbaum, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper
However, previous works followed evaluation settings consisting of older recognition models, limited cross-dataset and cross-model evaluations, and the use of low-scale testing data.
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.
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.
1 code implementation • 26 Nov 2021 • Philipp Terhörst, Malte Ihlefeld, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper
These variabilities can be measured in terms of face image quality which is defined over the utility of a sample for recognition.
Ranked #1 on Face Verification on IJB-B
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.
1 code implementation • 21 Oct 2021 • Philipp Terhörst, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper
To achieve this, a model-specific quality value of the input image is estimated and used to build a sample-specific quality regression model.
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 • 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 • 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.