Cover Image
Read Now

Deep Learning for Facial Informatics

Deep learning has been revolutionizing many fields in computer vision, and facial informatics is one of the major fields. Novel approaches and performance breakthroughs are often reported on existing benchmarks. As the performances on existing benchmarks are close to saturation, larger and more chal...

Full description

Bibliographic Details
Main Author: Hsu, Gee-Sern Jison
Other Authors: Timofte, Radu
Format: eBook
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:
Thermal Image
3d Geometry Data
Fused Cnn Feature
Face Liveness Detection
Deep Metric Learning
External Knowledge
Facial Landmarking
Convolutional Neural Networks
Coarse-to-fine
Emotion Classification
Facial Images Processing
Generative Adversarial Network
Deep Learning
Rgb
Facial Key Point Detection
History Of Engineering And Technology / Bicssc
Image Classification
Convolutional Neural Network (cnn)
Convolutional Neural Network
Age Estimation
2d Attribute Maps
Merging Networks
Depth
Multi-task Learning
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:Deep learning has been revolutionizing many fields in computer vision, and facial informatics is one of the major fields. Novel approaches and performance breakthroughs are often reported on existing benchmarks. As the performances on existing benchmarks are close to saturation, larger and more challenging databases are being made and considered as new benchmarks, further pushing the advancement of the technologies. Considering face recognition, for example, the VGG-Face2 and Dual-Agent GAN report nearly perfect and better-than-human performances on the IARPA Janus Benchmark A (IJB-A) benchmark. More challenging benchmarks, e.g., the IARPA Janus Benchmark A (IJB-C), QMUL-SurvFace and MegaFace, are accepted as new standards for evaluating the performance of a new approach. Such an evolution is also seen in other branches of face informatics. In this Special Issue, we have selected the papers that report the latest progresses made in the following topics: 1. Face liveness detection 2. Emotion classification 3. Facial age estimation 4. Facial landmark detection We are hoping that this Special Issue will be beneficial to all fields of facial informatics.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (102 p.)
ISBN:9783039369645
books978-3-03936-965-2
9783039369652

Similar Items