CSE 891-002: Deep Learning in Biometrics (original) (raw)

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

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