Search Results for author:
Found 19 papers, 4 papers with code
Data Pruning via Separability, Integrity, and Model Uncertainty-Aware Importance Sampling
This paper improves upon existing data pruning methods for image classification by introducing a novel pruning metric and pruning procedure based on importance sampling.
Minutiae-Guided Fingerprint Embeddings via Vision Transformers
We further demonstrate that by guiding the ViT to focus in on local, minutiae related features, we can boost the recognition performance.
Deep Convolutional Neural Networks in the Face of Caricature: Identity and Image Revealed
Deep convolutional neural networks (DCNNs) also create generalizable face representations, but with cascades of simulated neurons.
An Automatic System for Unconstrained Video-Based Face Recognition
In this work, we consider challenging scenarios for unconstrained video-based face recognition from multiple-shot videos and surveillance videos with low-quality frames.
A Proposal-Based Solution to Spatio-Temporal Action Detection in Untrimmed Videos
In this paper, we present a modular system for spatio-temporal action detection in untrimmed security videos.
A Fast and Accurate System for Face Detection, Identification, and Verification
We provide evaluation results of the proposed face detector on challenging unconstrained face detection datasets.
Localization: A Missing Link in the Pipeline of Object Matching and Registration
These approaches require object-centric images to perform matching.
Light-weight Head Pose Invariant Gaze Tracking
Unconstrained remote gaze tracking using off-the-shelf cameras is a challenging problem.
Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition
We show that integrating this simple step in the training pipeline significantly improves the performance of face verification and recognition systems.
Improving Network Robustness against Adversarial Attacks with Compact Convolution
In particular, we show that learning features in a closed and bounded space improves the robustness of the network.
The Do's and Don'ts for CNN-based Face Verification
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.
L2-constrained Softmax Loss for Discriminative Face Verification
In recent years, the performance of face verification systems has significantly improved using deep convolutional neural networks (DCNNs).
Ranked #4 on
Face Verification
on IJB-A
UMDFaces: An Annotated Face Dataset for Training Deep Networks
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.
An All-In-One Convolutional Neural Network for Face Analysis
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.
Ranked #9 on
Face Verification
on IJB-A
Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks
Over the last five years, methods based on Deep Convolutional Neural Networks (DCNNs) have shown impressive performance improvements for object detection and recognition problems.
HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition
We present an algorithm for simultaneous face detection, landmarks localization, pose estimation and gender recognition using deep convolutional neural networks (CNN).
Ranked #2 on
Face Detection
on Annotated Faces in the Wild
Face Alignment by Local Deep Descriptor Regression
We also present a face alignment algorithm based on regression using these local descriptors.
Towards the Design of an End-to-End Automated System for Image and Video-based Recognition
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.
A Deep Pyramid Deformable Part Model for Face Detection
We present a face detection algorithm based on Deformable Part Models and deep pyramidal features.
