Deep Learning-Based Face Analytics /

This book provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recogn...

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Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Ratha, Nalini K. (Editor), Patel, Vishal M. (Editor), Chellappa, Rama (Editor)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:	1st ed. 2021.
Series:	Advances in Computer Vision and Pattern Recognition,
Subjects:	Optical data processing. Biometrics (Biology). Machine learning. Neural networks (Computer science) . Image Processing and Computer Vision. Biometrics. Machine Learning. Mathematical Models of Cognitive Processes and Neural Networks. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

1. Deep CNN Face Recognition: Looking at the Past and the Future
2. Face Segmentation, Face Swapping, and Their Effect on Face Recognition
3. Disentangled Representation Learning and its Application to Face Analytics
4. Learning 3D Face Morphable Model from In-the-wild Images
5. Deblurring Face Images using Deep Networks
6. Blind-Superresolution of Faces for Surveillance
7. Hashing a Face.