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 interesting, and often unconventional approaches that can be applied to a broad set of areas including computer vision, machine learning, human biometrics, and the digital humanities. Specifically, my work is looking at open set recognition, extreme value theory models for visual recognition, biologically-inspired learning algorithms, and stylometry.


Walter J. Scheirer

Curriculum Vitae

PDF Format

Postdoctoral Fellows

Daniel Moreira

Graduate Students

Sreya Banerjee

Nathaniel Blanchard

Abigail Graese

Samuel Grieggs

Jeffery Kinnison

Derek Prijatelj

Brandon RichardWebster

Bingyu Shen

Rosaura Vidal Mata

William Theisen

Teaching

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

Recent Publications (see all)

  1. "Practical Text Phylogeny for Real-World Settings,"
    Bingyu Shen, Christopher W. Forstall, Anderson Rocha Walter J. Scheirer,
    IEEE Access,
    December 2018.
  2. "Flexible Learning-Free Segmentation and Reconstruction for Neuronal Circuit Tracing,"
    Ali Shahbazi, Jeffery Kinnison, Rafael Vescovi, Ming Du, Robert Hill, Maximilian Joesch,
    Marc Takeno, Hongkui Zeng, Nuno da Costa, Jaime Grutzendler, Narayanan Kasthuri,
    Walter J. Scheirer,
    Scientific Reports,
    Accepted for Publication September 2018.
  3. "Visual Psychophysics for Making Face Recognition Algorithms More Explainable,"
    Brandon RichardWebster, So Yon Kwon, Christopher Clarizio, Samuel E. Anthony,
    Walter J. Scheirer,
    Proceedings of the European Conference on Computer Vision (ECCV),
    September 2018.
  4. "Image Provenance Analysis at Scale,"
    Daniel Moreira, Aparna Bharati, Joel Brogan, Allan Pinto, Michael Parowski,
    Kevin Bowyer, Patrick Flynn, Anderson Rocha, Walter J. Scheirer,
    IEEE Transactions on Image Processing (T-IP),
    Accepted for Publication July 2018.
  5. "PsyPhy: A Psychophysics Driven Evaluation Framework for Visual Recognition,"
    Brandon RichardWebster, Samuel E. Anthony, Walter J. Scheirer,
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),
    Accepted for Publication June 2018.
  6. "The Limits and Potentials of Deep Learning for Robotics,"
    Niko Sunderhauf, Oliver Brock, Walter J. Scheirer, Raia Hadsell, Dieter Fox,
    Jurgen Leitner, Ben Upcroft, Pieter Abbeel, Wolfram Burgard, Michael Milford,
    Peter Corke,
    International Journal of Robotics Research,
    April 2018.
  7. "Using Human Brain Activity to Guide Machine Learning,"
    Ruth C. Fong, Walter J. Scheirer, David D. Cox,
    Scientific Reports,
    March 2018.
  8. "The Extreme Value Machine,"
    Ethan Rudd, Lalit P. Jain, Walter J. Scheirer, Terrance Boult,
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),
    March 2018.

New Research in arXiv / bioRxiv

  1. "Beyond Pixels: Image Provenance Analysis Leveraging Metadata,"
    Aparna Bharati, Daniel Moreira, Joel Brogan, Patricia Hale, Kevin Bowyer,
    Patrick Flynn, Anderson Rocha, Walter J. Scheirer,
    July 2018.
  2. "A Neurobiological Cross-domain Evaluation Metric for Predictive Coding Networks,"
    Nathaniel Blanchard, Jeffery Kinnison, Brandon RichardWebster, Pouya Bashivan,
    Walter J. Scheirer,
    May 2018.

Recent Projects (see all)

Hardware-Aware Distributed Hyperparameter Optimization

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
Image Restoration and Enhancement for Visual Recognition

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
Tools for Neuroscience

Tools for Neuroscience

Fall 2015 - Present

Techniques to help neuroscientists understand neuroanatomy and function

Keywords: connectomics, electron microscopy, two-photon imaging, x-ray tomography, 3D reconstruction
Brain-informed Machine Learning

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

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
Is good recognition metric?

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

Psychophysics for Computer Vision

Fall 2012 - Present

Measuring exemplar-by-exemplar dif´Čüculty and the pattern of errors of humans for supervised learning

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

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

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 and Literature

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

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)

Activities