CSE 891-002: Deep Learning in Biometrics

Overview

Course Description

This will be a seminar-style course where students will be assigned a number of papers to read. Students will then be expected to submit critiques for these papers as well as present these papers during the lecture. The papers will cover salient topics in biometrics and deep learning. These include concepts in face detection and alignment, face recognition, face anti-spoofing, iris recognition, fingerprint recognition and deep learning. The project component of this course will test the student’s ability to design deep learning solutions for biometrics applications. Please find syllabus here.

Optional Textbooks

This will be a seminar-style course, where students will be assigned a number of papers to read. The following textbooks are optional.

Tentative Schedule

Event Type Date Description Course Materials
Lecture 1 1/6 Introduction to Biometrics Slides
Lecture 2 1/8 Convolutional Neural Networks, part I
Homework 1 out
Slides
Pytorch-Image-Models
Homework 1
Lecture 3 1/13 Convolutional Neural Networks, part II Slides
ImageNet Training
Transfer Learning Tutorial
Bag of Tricks
Discussion 1/15 CNNs (Zachary McCullough)
Homework 1 due
Holiday 1/20 No Class
Lecture 4 1/22 Generative Adversarial Networks, part I
Homework 2 out
Slides
Homework 2
DCGAN
Lecture 5 1/27 Generative Adversarial Networks, part II Slides
CycleGAN and Pix2Pix
Discussion 1/29 GANs (Rahul Yalamanchili)
Homework 2 due
Lecture 6 2/3 Face Detection, part I
Homework 3 out
Slides
Homework 3
Lecture 7 2/5 Face Detection, part II Slides
Discussion 2/10 Face Detection (Madison Bowden)
Homework 3 due
Lecture 8 2/12 Face Alignment, part I
Homework 4 out
Slides
Homework 4
Lecture 9 2/17 Face Alignment, part II Slides
Menpo Benchmark
Pytorch_Face_Landmark
Discussion 2/19 Face Alignment (Jun Guo)
Homework 4 due
Lecture 10 2/24 Face Recognition, part I
Homework 5 out
Slides
Homework 5
Lecture 11 2/26 Face Recognition, part II
Slides
Spring Break 3/2 No Class
Spring Break 3/4 No Class
Discussion 3/9 Face Recognition (Shengjie Zhu)
Homework 5 due
Discussion 3/11 Face Recognition (Honglin Bao)
Final Project Proposal out
Lecture 12 3/16 Face Presentation Attack Detection, part I
Homework 6 out
Slides
Homework 6
CASIA-SURF
CASIA-SURF CeFA
Lecture 13 3/18 Face Presentation Attack Detection, part II Slides
Anti-spoofing @CVPR2019
Anti-spoofing @CVPR2020
Discussion 3/23 Face PAD (Andrew Hou)
Homework 6 due
Lecture 14 3/25 Fingerprint Recognition
Guest Lecture by Joshua Engelsma
Homework 7 out
Slides
Homework 7
Lecture 15 3/30 Fingerprint PAD
Guest Lecture by Joshua Engelsma
Slides
Discussion 4/1 Fingerprint
Homework 7 due
Lecture 16 4/6 Deepfakes
Guest Lecture by Dr. Antitza Dantcheva, INRIA
Homework 8 out
Slides
Homework 8
DeeperForensics-1.0
Discussion 4/8 3D Face Alignment (Ynsheng Masa Hu)
Lecture 18 4/13 Iris
Homework 8 due
Slides
Lecture 19 4/15 Cross-spectral Face Recognition
Guest Lecture by Dr. Benjamin Riggan, UNL
Polarimetric Thermal
Final Presentation 4/29 Final Project Report due

References: