Search Results for author: Rajeev Ranjan

Found 19 papers, 4 papers with code

Data Pruning via Separability, Integrity, and Model Uncertainty-Aware Importance Sampling

no code implementations20 Sep 2024 Steven Grosz, Rui Zhao, Rajeev Ranjan, Hongcheng Wang, Manoj Aggarwal, Gerard Medioni, Anil Jain

This paper improves upon existing data pruning methods for image classification by introducing a novel pruning metric and pruning procedure based on importance sampling.

Classification Image Classification

Minutiae-Guided Fingerprint Embeddings via Vision Transformers

no code implementations25 Oct 2022 Steven A. Grosz, Joshua J. Engelsma, Rajeev Ranjan, Naveen Ramakrishnan, Manoj Aggarwal, Gerard G. Medioni, Anil K. Jain

We further demonstrate that by guiding the ViT to focus in on local, minutiae related features, we can boost the recognition performance.

TAR

An Automatic System for Unconstrained Video-Based Face Recognition

no code implementations10 Dec 2018 Jingxiao Zheng, Rajeev Ranjan, Ching-Hui Chen, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa

In this work, we consider challenging scenarios for unconstrained video-based face recognition from multiple-shot videos and surveillance videos with low-quality frames.

Face Recognition

Light-weight Head Pose Invariant Gaze Tracking

no code implementations23 Apr 2018 Rajeev Ranjan, Shalini De Mello, Jan Kautz

Unconstrained remote gaze tracking using off-the-shelf cameras is a challenging problem.

Gaze Estimation Transfer Learning +1

Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition

no code implementations3 Apr 2018 Rajeev Ranjan, Ankan Bansal, Hongyu Xu, Swami Sankaranarayanan, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa

We show that integrating this simple step in the training pipeline significantly improves the performance of face verification and recognition systems.

Face Verification

Improving Network Robustness against Adversarial Attacks with Compact Convolution

no code implementations3 Dec 2017 Rajeev Ranjan, Swami Sankaranarayanan, Carlos D. Castillo, Rama Chellappa

In particular, we show that learning features in a closed and bounded space improves the robustness of the network.

Face Verification

The Do's and Don'ts for CNN-based Face Verification

no code implementations21 May 2017 Ankan Bansal, Carlos Castillo, Rajeev Ranjan, Rama Chellappa

While the research community appears to have developed a consensus on the methods of acquiring annotated data, design and training of CNNs, many questions still remain to be answered.

Face Recognition Face Verification

L2-constrained Softmax Loss for Discriminative Face Verification

1 code implementation28 Mar 2017 Rajeev Ranjan, Carlos D. Castillo, Rama Chellappa

In recent years, the performance of face verification systems has significantly improved using deep convolutional neural networks (DCNNs).

Face Verification

UMDFaces: An Annotated Face Dataset for Training Deep Networks

1 code implementation4 Nov 2016 Ankan Bansal, Anirudh Nanduri, Carlos Castillo, Rajeev Ranjan, Rama Chellappa

Recent progress in face detection (including keypoint detection), and recognition is mainly being driven by (i) deeper convolutional neural network architectures, and (ii) larger datasets.

Face Detection Face Recognition +1

An All-In-One Convolutional Neural Network for Face Analysis

1 code implementation3 Nov 2016 Rajeev Ranjan, Swami Sankaranarayanan, Carlos D. Castillo, Rama Chellappa

The proposed method employs a multi-task learning framework that regularizes the shared parameters of CNN and builds a synergy among different domains and tasks.

Age Estimation Face Alignment +5

Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks

no code implementations9 May 2016 Jun-Cheng Chen, Rajeev Ranjan, Swami Sankaranarayanan, Amit Kumar, Ching-Hui Chen, Vishal M. Patel, Carlos D. Castillo, Rama Chellappa

Over the last five years, methods based on Deep Convolutional Neural Networks (DCNNs) have shown impressive performance improvements for object detection and recognition problems.

Face Detection Face Recognition +3

HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition

2 code implementations3 Mar 2016 Rajeev Ranjan, Vishal M. Patel, Rama Chellappa

We present an algorithm for simultaneous face detection, landmarks localization, pose estimation and gender recognition using deep convolutional neural networks (CNN).

Face Detection Multi-Task Learning +1

Face Alignment by Local Deep Descriptor Regression

no code implementations29 Jan 2016 Amit Kumar, Rajeev Ranjan, Vishal Patel, Rama Chellappa

We also present a face alignment algorithm based on regression using these local descriptors.

Face Alignment regression

Towards the Design of an End-to-End Automated System for Image and Video-based Recognition

no code implementations28 Jan 2016 Rama Chellappa, Jun-Cheng Chen, Rajeev Ranjan, Swami Sankaranarayanan, Amit Kumar, Vishal M. Patel, Carlos D. Castillo

In this paper, we present a brief history of developments in computer vision and artificial neural networks over the last forty years for the problem of image-based recognition.

Face Verification Object +3

A Deep Pyramid Deformable Part Model for Face Detection

no code implementations18 Aug 2015 Rajeev Ranjan, Vishal M. Patel, Rama Chellappa

We present a face detection algorithm based on Deformable Part Models and deep pyramidal features.

Face Detection Robust Face Recognition

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