Walter J. Scheirer

walter.scheirer@nd.edu, @wjscheirer

Dennis O. Doughty Associate Professor in the Department of Computer Science and Engineering,
University of Notre Dame

Research Overview

My research is primarily focused around the problem of recognition, including the representations and algorithms supporting solutions to it. I am particularly interested in features and learning-based methods that apply to both vision and language, thus breaking away from the persistent compartmentalization of recognition tasks (something hinted at by David Marr over 30 years ago). This has led to some intriguing and often unconventional approaches that can be applied to a broad set of areas within artificial intelligence including computer vision, machine learning, and human biometrics. Specifically, my work is looking at open set recognition, extreme value theory models for visual recognition, and biologically-inspired learning algorithms.

Curriculum Vitae

PDF Format

Postdoctoral Fellows

Megan Levis
K. D. Gayan Maduranga (Co-Advised with Jonathan Hauenstein)
Michael Yankoski (Co-Advised with Tim Weninger)

Graduate Students

Samuel Grieggs

Jin Huang

Jeffery Kinnison

Priscila Moreira

Derek Prijatelj

Rosaura Vidal Mata (Co-Advised with Kevin Bowyer)

William Theisen

Teaching

Spring 2022: CSE 40175 Ethical & Professional Issues

Fall 2021: CSE 40175 Ethical & Professional Issues

Spring 2020: CSE 40567/60567 Computer Security

Fall 2019: CSE 40171 Artificial Intelligence

Spring 2019: CSE 40567/60567 Computer Security

Fall 2018: CSE 40171 Artificial Intelligence

Spring 2018: CSE 40567/44567/60567 Computer Security

Spring 2017: CSE 40567/60567 Computer Security

Spring 2016: CSE 40567/60567 Computer Security

Fall 2015: CSE 40537/60537 Biometrics

Books

Coming Soon: Restyling Reality: A History of Fake Things on the Internet (Stanford University Press)

Quantitative Intertextuality: Analyzing the Markers of Information Reuse (Springer-Nature) with Christopher W. Forstall

Extreme Value Theory-based Methods for Visual Recognition (Morgan & Claypool Publishers)

Recent Publications (see all)

"Bridging the Gap Between Computational Photography and Visual
Recognition,"
Rosaura G. VidalMata, Sreya Banerjee, Brandon RichardWebster, Michael Albright,
Pedro Davalos, Scott McCloskey, Ben Miller, Asong Tambo, Sushobhan Ghosh,
Sudarshan Nagesh, Ye Yuan, Yueyu Hu, Junru Wu, Wenhan Yang, Xiaoshuai Zhang,
Jiaying Liu, Zhangyang Wang, Hwann-Tzong Chen, Tzu-Wei Huang, Wen-Chi Chin,
Yi-Chun Li, Mahmoud Lababidi, Charles Otto, Walter J. Scheirer,
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),

December 2021.

[pdf]
[bibtex]
@article{vidalmata2021bridging,
title = {Bridging the Gap Between Computational Photography and Visual
Recognition},
author = {Rosaura G. VidalMata and
Sreya Banerjee and
Brandon RichardWebster and
Michael Albright and
Pedro Davalos and
Scott McCloskey and
Ben Miller and
Asong Tambo and
Sushobhan Ghosh and
Sudarshan Nagesh and
Ye Yuan and
Yueyu Hu and
Junru Wu and
Wenhan Yang and
Xiaoshuai Zhang and
Jiaying Liu and
Zhangyang Wang and
Hwann-Tzong Chen and
Tzu-Wei Huang and
Wen-Chi Chin and
Yi-Chun Li and
Mahmoud Lababidi and
Charles Otto and
Walter J. Scheirer},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence
(T-PAMI)},
volume = {43},
number = {12},
month = {December},
year = {2021}
}
"A Study of the Human Perception of Synthetic Faces,"
Bingyu Shen, Brandon RichardWebster, Alice O'Toole, Kevin Bowyer,
Walter J. Scheirer,
Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition (FG),

December 2021.

[pdf]
[bibtex]
@inproceedings{Shen_FG2021,
author = {Bingyu Shen and
Brandon RichardWebster and
Alice O'Toole and
Kevin Bowyer and
Walter J. Scheirer},
title = {A Study of the Human Perception of Synthetic Faces},
booktitle = {Proceedings of the IEEE Conference on Automatic Face
and Gesture Recognition (FG)},
year = {2021}
}
"A Bayesian Evaluation Framework for Ground Truth-Free Visual Recognition
Tasks,"
Derek Prijatelj, Mel McCurie, Samuel Anthony, Walter J. Scheirer,
Pattern Recognition,

Accepted for Publicatiton in October 2021.

[pdf]
[bibtex]
@misc{Prijatelj2020Evaluation,
title={A Bayesian Evaluation Framework for Ground Truth-Free Visual
Recognition Tasks},
author={Derek Prijatelj and Mel McCurie and Samuel Anthony and Walter Scheirer},
year={2020},
eprint={2007.06711},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
"Handwriting Recognition with Novelty,"
Derek Prijatelj, Samuel Grieggs, Futoshi Yumoto, Eric Robertson, Walter J. Scheirer,
International Conference on Document Analysis and Recognition (ICDAR),

September 2021.

[pdf]
[bibtex]
@inproceedings{Prijatelj_ICDAR2021,
author = {Derek Prijatelj and
Samuel Grieggs and
Futoshi Yumoto and
Eric Robertson and
Walter J. Scheirer},
title = {Handwriting Recognition with Novelty},
booktitle = {International Conference on Document Analysis and Recognition
(ICDAR},
year = {2021}
}
"Fast Local Spatial Verification for Feature-Agnostic Large-Scale Image Retrieval,"
Joel Brogan, Aparna Bharati, Daniel Moreira, Kevin Bowyer, Patrick Flynn,
Anderson Rocha, Walter J. Scheirer,
IEEE Transactions on Image Processing (T-IP),

July 2021.

[pdf]
[bibtex]
@article{Brogan_TIP21,
author = {Joel Brogan and
Aparna Bharati and
Daniel Moreira and
Kevin W. Bowyer and
Patrick J. Flynn and
Anderson Rocha and
Walter J. Scheirer},
title = {Fast Local Spatial Verification for Feature-Agnostic Large-Scale
Image Retrieval},
journal = {IEEE Transactions on Image Processing (T-IP)},
volume = {30},
year = {2021}
}
"Measuring Human Perception to Improve Handwritten Document Transcription,"
Samuel Grieggs, Bingyu Shen, Greta Rauch, Pei Li, Jiaqi Ma, David Chiang,
Brian Price, Walter J. Scheirer,
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),

Accepted for Publicatiton in June 2021.

[pdf]
[bibtex]
@article{DBLP:journals/corr/abs-1904-03734,
author = {Samuel Grieggs and
Bingyu Shen and
Greta Rauch and
Pei Li and
Jiaqi Ma and
David Chiang and
Brian Price and
Walter J. Scheirer},
title = {Measuring Human Perception to Improve Handwritten Document
Transcription},
journal = {CoRR},
volume = {abs/1904.03734},
year = {2020},
url = {http://arxiv.org/abs/1904.03734},
archivePrefix = {arXiv},
eprint = {1904.03734},
}
"Automatic Discovery of Political Meme Genres with Diverse Appearances,"
William Theisen, Joel Brogan, Pamela Bilo Thomas, Daniel Moreira, Pascal Phoa,
Tim Weninger, Walter J. Scheirer,
Proceedings of the International AAAI Conference on Web and Social Media (ICWSM),

June 2021.

[pdf] [code] [data]
[bibtex]
@inproceedings{theisen2021automatic,
title={Automatic Discovery of Political Meme Genres with Diverse Appearances},
author={William Theisen and Joel Brogan and Pamela Bilo Thomas and
Daniel Moreira and Pascal Phoa and Tim Weninger and Walter Scheirer},
booktitle={International AAAI Conference on Web and Social Media (ICWSM)}
year={2021},
}
"Towards a Unifying Framework for Formal Theories of Novelty,"
Terrance Boult, Przemyslaw Grabowicz, Derek Prijatelj, Roni Stern, Lawrence Holder,
Joshua Alspector, Mohsen Jafarzadeh, Touqeer Ahmad, Akshay Dhamija, Chunchun Li,
Steve Cruz, Abhinav Shrivastava, Carl Vondrick, Walter J. Scheirer,
AAAI Conference on Artificial Intelligence (AAAI 2021), Senior Member Track,

February 2021.

[pdf]
[bibtex]
@inproceedings{Boult21,
author = {Terrance Boult and
Przemyslaw Grabowicz and
Derek Prijatelj and
Lawrence Holder and
Joshua Alspector and
Mohsen Jafarzadeh and
Touqeer Ahmad and
Akshay Dhamija and
Chunchun Li and
Steve Cruz and
Abhinav Shrivastava and
Carl Vondrick and
Walter J. Scheirer},
title = {Towards a Unifying Framework for Formal Theories of Novelty},
booktitle = {AAAI Conference on Artificial Intelligence (AAAI 2021)},
year = {2021},
}
"The Criminality From Face Illusion,"
Kevin Bowyer, Michael King, Walter J. Scheirer, Kushal Vangara,
IEEE Transactions on Technology and Society (T-TS),

December 2020.

[pdf]
[bibtex]
@article{bowyer2020criminality,
title={The Criminality From Face Illusion},
author={Kevin W. Bowyer and Michael King and Walter Scheirer and Kushal Vangara},
journal={IEEE Transactions on Technology and Society (T-TS)},
volume={1},
number={4},
month={December},
year={2020},
}
"A Pandemic of Bad Science,"
Walter J. Scheirer,
Bulletin of the Atomic Scientists,

July 2020.

[pdf]
[bibtex]
@article{scheirer2020pandemic,
title={A Pandemic of Bad Science},
author={Scheirer, Walter},
journal={Bulletin of the Atomic Scientists},
volume={76},
number={4},
month={July},
year={2020},
publisher={Taylor \& Francis}
}
"The Next Generation of Human-Drone Partnerships: Co-Designing an
Emergency Response System,"
Ankit Agrawal, Sophia Abraham, Benjamin Burger, Chichi Christine, Luke Fraser,
John Hoeksema, Sara Hwang, Elizabeth Travnik, Shreya Kumar, Walter J. Scheirer,
Jane Cleland-Huang, Michael Vierhauser,
Ryan Bauer, Steve Cox,
Proceedings of the ACM CHI Conference on Human Factors in Computing Systems
(Honorable Mention Award),

April 2020.

[pdf]
[bibtex]
@misc{agrawal2020generation,
title={The Next Generation of Human-Drone Partnerships: Co-Designing an
Emergency Response System},
author={Ankit Agrawal and Sophia Abraham and Benjamin Burger and
Chichi Christine and Luke Fraser and John Hoeksema and Sara Hwang and
Elizabeth Travnik and Shreya Kumar and Walter Scheirer and
Jane Cleland-Huang and Michael Vierhauser and Ryan Bauer and Steve Cox},
year={2020},
eprint={2001.03849},
archivePrefix={arXiv},
primaryClass={cs.HC}
}

New Research in arXiv / bioRxiv

"Forensic Analysis of Synthetically Generated Scientific Images,"
Sara Mandelli, Davide Cozzolino, Joao P. Cardenuto, Daniel Moreira, Paolo Bestagini,
Walter J. Scheirer, Anderson Rocha, Luisa Verdoliva, Stefano Tubaro, Edward J. Delp,
December 2021.

[pdf]
[bibtex]
@misc{mandelli2021forensic,
title={Forensic Analysis of Synthetically Generated Scientific Images},
author={Sara Mandelli and Davide Cozzolino and Joao P. Cardenuto
and Daniel Moreira and Paolo Bestagini and Walter Scheirer and
Anderson Rocha and Luisa Verdoliva and Stefano Tubaro and Edward J. Delp},
year={2021},
eprint={2112.08739},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
"On the Objective Evaluation of Post Hoc Explainers,"
Zachariah Carmichael, Walter J. Scheirer,
June 2021.

[pdf]
[bibtex]
@misc{carmichael2021objective,
title={On the Objective Evaluation of Post Hoc Explainers},
author={Zachariah Carmichael and Walter J. Scheirer},
year={2021},
eprint={2106.08376},
archivePrefix={arXiv},
primaryClass={cs.LG}
}

Recent Projects (see all)

Practical Technology Ethics

Fall 2019 - Present

Constructive criticism of emerging technologies, scientific trends, and policies

Keywords: machine learning, facial analysis, election integrity, scientific integrity, peace studies

Human-Drone Partnerships for Emergency Response

Fall 2019 - Present

Semi-autonomous UAVs to support emergency response scenarios, such as fire surveillance and search and rescue

Keywords: drones, software engineering, participatory design, object detection, first responders

Unconventional Approaches to Hacking Neural Networks

Spring 2018 - Present

Uncovering new vulnerabilities in neural network-based applications where security is a consideration

Keywords: machine learning, neural networks, face recognition, security, backdoors, exploits

Hardware-Aware Distributed Hyperparameter Optimization

Spring 2017 - Present

Intelligent mapping of hardware resources to model search tasks

Keywords: machine learning, hyperparameters, optimization, distributed computing, connectomics

Computational Models of Zebrafish Sensory Integration

Fall 2016 - Fall 2020

Modeling neural circuits to explain fish behavior and apply to generalized recognition problems in AI

Keywords: computational neuroscience, zebrafish, sensory integration, data fusion, extreme value theory

Image Restoration and Enhancement for Visual Recognition

Fall 2016 - Present

Work to bridge the gap between computational photography and visual recognition

Keywords: deblurring, denoising, super-resolution, deep learning, object recognition, video

Face Synthesis

Fall 2015 - Present

Fast and accurate photo-quality face synthesis for use in face recognition work

Keywords: face synthesis, face recognition, face analysis, computer graphics, data augmentation

Learning-free Image Segmentation

Fall 2015 - Present

Image segmentation for settings where machine learning-based approaches are slow and do not generalize

Keywords: image filtering, volumetric segmentation, connectomics, medical imaging, iris recognition

Tools for Neuroscience

Fall 2015 - Present

Techniques to help neuroscientists understand neuroanatomy and function

Keywords: connectomics, electron microscopy, two-photon imaging, x-ray tomography, behavior

Brain-informed Machine Learning

Fall 2014 - Present

Applying measurements of neural activity to regularize machine learning models

Keywords: fMRI, psychophysics, classification, deep learning, neural-weights, object recognition

Visual Place Recognition

Spring 2013 - Present

Condition invariant visual place recognition for robot navigation inspired by vision science

Keywords: robotics, navigation, place recognition, whole image matching, patch matching, calibration

Good Recognition is Non-metric

Fall 2012 - Spring 2014

A new look at a fundamental question in computer vision: is recognition metric?

Keywords: machine learning, metric learning, recognition, face recognition, object recognition

Psychophysics for Computer Vision

Fall 2012 - Present

Measuring exemplar-by-exemplar difﬁculty and the pattern of errors of humans for supervised learning

Keywords: machine learning, psychology, citizen science, psychophysics, face detection, attributes

Open Set Recognition

Spring 2011 - Present

Theory and algorithms that address the difficult problem of training without complete class knowledge

Keywords: machine learning, object recognition, face recognition, support vector machines, 1-vs-set machine

Extreme Value Theory for Visual Recognition

Spring 2008 - Present

The theory and practice of recognition score analysis for prediction and fusion

Keywords: calibration, meta-recognition, score analysis, object recognition, face recognition, attributes

Language & Literature

Spring 2009 - Present

Machine learning and related statistical methods to improve the process by which intertextuality is studied

Keywords: computational linguistics, intertextuality, sound, stylistics, classics, authorship attribution

Digital Image and Video Forensics

Spring 2008 - Present

Approaches to steganalysis, forgery detection and sensor fingerprinting

Keywords: forensics, forgery detection, data hiding, source identification, sensor fingerprinting

Recent Talks (see all)

Invited talk at the Computational Research Integrity Conference (CRI-CONF 21): Understanding the Provenance of Visual Disinformation Targeting Science
Invited talk at the IEEE International Symposium on Technology and Society Conference (ISTAS 20): The 'Criminality from Face' Illusion
Invited talk at the WACV 2020 Workshop Neural Architecture Search for Computer Vision in the Wild: Representational Dissimilarity Analysis as a Tool for Neural Network Model Search
Talk at the 2019 Beijing Forum Panel on Humanity and Legal Governance in the Digital Era: New Perspectives on Digital Media Integrity
Keynote talk at the 18th International Conference of the Biometrics Special Interest Group (BIOSIG 2019): The Limits and Potentials of Deep Learning for Facial Analysis
Talk at the DEF CON 27 AI Village: Backdooring Convolutional Neural Networks with Targeted Weight Perturbations
Invited talk at the CVPR 2018 Workshop "Real-World Challenges and New Benchmarks for Deep Learning in Robotic Vision":
A Psychophysics Driven Evaluation Framework for Visual Recognition
Invited talk at Cultural Analytics 2017: Quantitative Intertextuality: Analyzing the Markers of Information Reuse
Invited talk at Argonne National Laboratory: Scalable Strategies for Image Analysis in Neuroscience
CVPR 2016 Tutorial: Statistical Methods for Open Set Recognition
Invited talk at the RSS 2016 Workshop "Are the Sceptics Right? Limits and Potentials of Deep Learning in Robotics":
The Impact of the Open Set Recognition Problem on Deep Learning (Video)

Activities

CVPR 2022 will be held as a hybrid meeting online and in New Orleans, June 19th - 24th
WACV 2022 was held as a hybrid meeting online and in Waikoloa, HI, January 4th - 8th (yes we actually made it to Hawaii)
The UG^2+ Challenge prize challenge workshop on image restoration and enhancement was held at CVPR 2019
The Interactive and Adaptive Learning in an Open World workshop was co-located with ECCV 2018
The UG^2 Challenge prize challenge workshop on image restoration and enhancement was held at CVPR 2018
Join the PAMI-TC (now on LinkedIn) and the Computer Vision Foundation