Search Results for author: Kiran Raja

Found 34 papers, 10 papers with code

Uncertainty-Aware Regularization for Image-to-Image Translation

no code implementations24 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.

Image-to-Image Translation Translation

Capsule Endoscopy Multi-classification via Gated Attention and Wavelet Transformations

no code implementations25 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.

Specificity

SynMorph: Generating Synthetic Face Morphing Dataset with Mated Samples

no code implementations9 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.

Face Image Quality Face Image Quality Assessment +2

Towards Inclusive Face Recognition Through Synthetic Ethnicity Alteration

no code implementations2 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.

Diversity Face Image Quality +4

NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results

3 code implementations22 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.

4k Low-Light Image Enhancement +1

E2F-Net: Eyes-to-Face Inpainting via StyleGAN Latent Space

2 code implementations18 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.

Face Recognition Facial Inpainting +1

Towards minimizing efforts for Morphing Attacks -- Deep embeddings for morphing pair selection and improved Morphing Attack Detection

no code implementations29 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.

Face Recognition

A Latent Fingerprint in the Wild Database

no code implementations3 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.

Benchmarking

Learning Pairwise Interaction for Generalizable DeepFake Detection

1 code implementation26 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.

Decision Making DeepFake Detection +2

Analyzing Fairness in Deepfake Detection With Massively Annotated Databases

4 code implementations11 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.

Attribute Decision Making +3

On the (Limited) Generalization of MasterFace Attacks and Its Relation to the Capacity of Face Representations

no code implementations23 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.

Face Recognition Fairness

Analyzing Human Observer Ability in Morphing Attack Detection -- Where Do We Stand?

no code implementations24 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.

MORPH

Generation of Non-Deterministic Synthetic Face Datasets Guided by Identity Priors

no code implementations7 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.

Face Image Quality Face Recognition

QMagFace: Simple and Accurate Quality-Aware Face Recognition

1 code implementation26 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.

Face Image Quality Face Recognition +1

Algorithmic Fairness in Face Morphing Attack Detection

no code implementations23 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.

Face Morphing Attack Detection Face Recognition +2

Pixel-Level Face Image Quality Assessment for Explainable Face Recognition

1 code implementation21 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.

Face Image Quality Face Image Quality Assessment +1

ReGenMorph: Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation

no code implementations20 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.

Face Recognition Generative Adversarial Network

On the Applicability of Synthetic Data for Face Recognition

no code implementations6 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.

Face Image Quality Face Image Quality Assessment +2

Face Morphing Attack Generation & Detection: A Comprehensive Survey

no code implementations3 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.

Benchmarking Face Recognition +2

On Benchmarking Iris Recognition within a Head-mounted Display for AR/VR Application

no code implementations20 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.

Benchmarking Iris Recognition

MIPGAN -- Generating Strong and High Quality Morphing Attacks Using Identity Prior Driven GAN

no code implementations3 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.

Face Generation Face Recognition +2

On the Influence of Ageing on Face Morph Attacks: Vulnerability and Detection

no code implementations6 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.

Face Recognition MORPH

Smartphone Multi-modal Biometric Authentication: Database and Evaluation

no code implementations5 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.

Diversity

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