Search Results for author: Aditya Nigam

Found 26 papers, 4 papers with code

Is Sharing of Egocentric Video Giving Away Your Biometric Signature?

no code implementations ECCV 2020 Daksh Thapar, Chetan Arora, Aditya Nigam

In this work, we create a novel kind of privacy attack by extracting the wearer’s gait profile, a well known biometric signature, from such optical flow in the egocentric videos.

Optical Flow Estimation

Impact of Iris Pigmentation on Performance Bias in Visible Iris Verification Systems: A Comparative Study

no code implementations13 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.

Iris Recognition

Tract-RLFormer: A Tract-Specific RL policy based Decoder-only Transformer Network

no code implementations8 Nov 2024 Ankita Joshi, Ashutosh Sharma, Anoushkrit Goel, Ranjeet Ranjan Jha, Chirag Ahuja, Arnav Bhavsar, Aditya Nigam

Fiber tractography is a cornerstone of neuroimaging, enabling the detailed mapping of the brain's white matter pathways through diffusion MRI.

Decoder reinforcement-learning +1

Synthetic Forehead-creases Biometric Generation for Reliable User Verification

1 code implementation28 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).

SSIM

FH-SSTNet: Forehead Creases based User Verification using Spatio-Spatial Temporal Network

no code implementations24 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.

Management Triplet

Merry Go Round: Rotate a Frame and Fool a DNN

no code implementations CVPR 2022 Daksh Thapar, Aditya Nigam, Chetan Arora

On the other hand DNNs are known to be susceptible to Adversarial Attacks (AAs) which add im-perceptible noise to the input.

Action Detection Activity Detection +1

Anonymizing Egocentric Videos

no code implementations ICCV 2021 Daksh Thapar, Aditya Nigam, Chetan Arora

In a more damaging scenario, one can even recognize a wearer using hand gestures from egocentric videos, or identify a wearer in third person videos such as from a surveillance camera.

Activity Recognition object-detection +2

IHashNet: Iris Hashing Network based on efficient multi-index hashing

no code implementations7 Dec 2020 Avantika Singh, Chirag Vashist, Pratyush Gaurav, Aditya Nigam, Rameshwar Pratap

Here, in this paper, we propose an iris indexing scheme using real-valued deep iris features binarized to iris bar codes (IBC) compatible with the indexing structure.

Computational Efficiency

UESegNet: Context Aware Unconstrained ROI Segmentation Networks for Ear Biometric

no code implementations8 Oct 2020 Aman Kamboj, Rajneesh Rani, Aditya Nigam, Ranjeet Ranjan Jha

It has been observed that the proposed models UESegNet-1 and UESegNet-2 outperformed the FRCNN and SSD at higher values of IOUs i. e. an accuracy of 100\% is achieved at IOU 0. 5 on majority of the databases.

object-detection Object Detection +1

Semantic Features Aided Multi-Scale Reconstruction of Inter-Modality Magnetic Resonance Images

1 code implementation22 Jun 2020 Preethi Srinivasan, Prabhjot Kaur, Aditya Nigam, Arnav Bhavsar

Long acquisition time (AQT) due to series acquisition of multi-modality MR images (especially T2 weighted images (T2WI) with longer AQT), though beneficial for disease diagnosis, is practically undesirable.

Decoder

SP-NET: One Shot Fingerprint Singular-Point Detector

no code implementations13 Aug 2019 Geetika Arora, Ranjeet Ranjan Jha, Akash Agrawal, Kamlesh Tiwari, Aditya Nigam

Singular points of a fingerprint image are special locations having high curvature properties.

FKIMNet: A Finger Dorsal Image Matching Network Comparing Component (Major, Minor and Nail) Matching with Holistic (Finger Dorsal) Matching

no code implementations2 Apr 2019 Daksh Thapar, Gaurav Jaswal, Aditya Nigam

In distinguished experiments, the individual performance of finger, as well as weighted sum score level fusion of major knuckle, minor knuckle, and nail modalities have been computed, justifying our assumption to consider full finger as biometrics instead of its counterparts.

Data Augmentation Triplet

FDSNet: Finger dorsal image spoof detection network using light field camera

no code implementations18 Dec 2018 Avantika Singh, Gaurav Jaswal, Aditya Nigam

At present spoofing attacks via which biometric system is potentially vulnerable against a fake biometric characteristic, introduces a great challenge to recognition performance.

Finger Dorsal Image Spoof Detection Transfer Learning

FDFNet : A Secure Cancelable Deep Finger Dorsal Template Generation Network Secured via. Bio-Hashing

2 code implementations13 Dec 2018 Avantika Singh, Ashish Arora, Shreya Hasmukh Patel, Gaurav Jaswal, Aditya Nigam

In this work, we have proposed a secure cancelable finger dorsal template generation network (learning domain specific features) secured via.

Management

Learning to Decode 7T-like MR Image Reconstruction from 3T MR Images

no code implementations18 Jun 2018 Aditya Sharma, Prabhjot Kaur, Aditya Nigam, Arnav Bhavsar

Increasing demand for high field magnetic resonance (MR) scanner indicates the need for high-quality MR images for accurate medical diagnosis.

Decoder Image Reconstruction +1

Siamese LSTM based Fiber Structural Similarity Network (FS2Net) for Rotation Invariant Brain Tractography Segmentation

no code implementations28 Dec 2017 Shreyas Malakarjun Patil, Aditya Nigam, Arnav Bhavsar, Chiranjoy Chattopadhyay

In this paper, we propose a novel deep learning architecture combining stacked Bi-directional LSTM and LSTMs with the Siamese network architecture for segmentation of brain fibers, obtained from tractography data, into anatomically meaningful clusters.

Segmentation

GHCLNet: A Generalized Hierarchically tuned Contact Lens detection Network

no code implementations14 Oct 2017 Avantika Singh, Vishesh Mistry, Dhananjay Yadav, Aditya Nigam

The proposed architecture results are quite promising and outperforms the available state-of-the-art lens detection algorithms.

BrainSegNet : A Segmentation Network for Human Brain Fiber Tractography Data into Anatomically Meaningful Clusters

no code implementations14 Oct 2017 Tushar Gupta, Shreyas Malakarjun Patil, Mukkaram Tailor, Daksh Thapar, Aditya Nigam

The segregation of brain fiber tractography data into distinct and anatomically meaningful clusters can help to comprehend the complex brain structure and early investigation and management of various neural disorders.

Classification General Classification +1

VGR-Net: A View Invariant Gait Recognition Network

no code implementations13 Oct 2017 Daksh Thapar, Divyansh Aggarwal, Punjal Agarwal, Aditya Nigam

It is a 2-stage network, in which we have a classification network that initially identifies the viewing point angle.

Gait Recognition Person Identification

UBSegNet: Unified Biometric Region of Interest Segmentation Network

no code implementations26 Sep 2017 Ranjeet Ranjan Jha, Daksh Thapar, Shreyas Malakarjun Patil, Aditya Nigam

In this paper, we have proposed a novel end-to-end, Unified Biometric ROI Segmentation Network (UBSegNet), for extracting region of interest from five different biometric traits viz.

General Classification Management +1

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