most citedMinutiae-Guided Fingerprint Embeddings via Vision Transformers

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cs.CV20229 cited

Minutiae-Guided Fingerprint Embeddings via Vision Transformers

Steven A. Grosz, Joshua J. Engelsma, Rajeev Ranjan +4

Minutiae matching has long dominated the field of fingerprint recognition. However, deep networks can be used to extract fixed-length embeddings from fingerprints. To date, the few…

cs.CV2018

Deep Convolutional Neural Networks in the Face of Caricature: Identity and Image Revealed

Matthew Q. Hill, Connor J. Parde, Carlos D. Castillo +5

Real-world face recognition requires an ability to perceive the unique features of an individual face across multiple, variable images. The primate visual system solves the problem…

cs.CV2018

An Automatic System for Unconstrained Video-Based Face Recognition

Jingxiao Zheng, Rajeev Ranjan, Ching-Hui Chen +3

Although deep learning approaches have achieved performance surpassing humans for still image-based face recognition, unconstrained video-based face recognition is still a challeng…

cs.CV2018

A Proposal-Based Solution to Spatio-Temporal Action Detection in Untrimmed Videos

Joshua Gleason, Rajeev Ranjan, Steven Schwarcz +3

Existing approaches for spatio-temporal action detection in videos are limited by the spatial extent and temporal duration of the actions. In this paper, we present a modular syste…

cs.CV2018

A Fast and Accurate System for Face Detection, Identification, and Verification

Rajeev Ranjan, Ankan Bansal, Jingxiao Zheng +7

The availability of large annotated datasets and affordable computation power have led to impressive improvements in the performance of CNNs on various object detection and recogni…

cs.CV2018

Localization: A Missing Link in the Pipeline of Object Matching and Registration

Deepak Mishra, Rajeev Ranjan, Santanu Chaudhury +2

Image registration is a process of aligning two or more images of same objects using geometric transformation. Most of the existing approaches work on the assumption of location in…