16 citations · 32 across the 4 of their papers we have counts for
10 papers
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…
ExpNet: Landmark-Free, Deep, 3D Facial Expressions
Feng-Ju Chang, Anh Tuan Tran, Tal Hassner +3
We describe a deep learning based method for estimating 3D facial expression coefficients. Unlike previous work, our process does not relay on facial landmark detection methods as…
FacePoseNet: Making a Case for Landmark-Free Face Alignment
Fengju Chang, Anh Tuan Tran, Tal Hassner +3
We show how a simple convolutional neural network (CNN) can be trained to accurately and robustly regress 6 degrees of freedom (6DoF) 3D head pose, directly from image intensities.…
Deep 3D Face Identification
Donghyun Kim, Matthias Hernandez, Jongmoo Choi +1
We propose a novel 3D face recognition algorithm using a deep convolutional neural network (DCNN) and a 3D augmentation technique. The performance of 2D face recognition algorithms…
Pooling Faces: Template based Face Recognition with Pooled Face Images
Tal Hassner, Iacopo Masi, Jungyeon Kim +4
We propose a novel approach to template based face recognition. Our dual goal is to both increase recognition accuracy and reduce the computational and storage costs of template ma…
Capturing Dynamic Textured Surfaces of Moving Targets
Ruizhe Wang, Lingyu Wei, Etienne Vouga +4
We present an end-to-end system for reconstructing complete watertight and textured models of moving subjects such as clothed humans and animals, using only three or four handheld…