Speakers
Tim Andrews, University of York, UK
Face Recognition under Natural Viewing: The Integration of Perception and Person Knowledge
Daniel Carragher, University of Adelaide, Australia
The Performance of Human-algorithm Teams on One-to-one Verification Tasks
Amy Dawel, Australian National University, Australia.
When Bias Helps: Implicit Training Improves Human Detection of AI-generated Faces
Katharina Dobs, Justis Liebig University, Germany
Functional Specialization for Faces and Bodies in Brains and DNNs
James Dunn, University of New South Wales, Australia
Too Good to be True: Synthetic AI Faces are More Average than Real Faces and Super-recognisers Know It
Ida Gobbini, University of Bologna, Italy
Use of naturalistic stimuli to investigate the face perception system
Peter Hancock, Stirling University, Scotland
Islands of Expertise
Leyla Isik, Johns Hopkins University, USA
Relational Visual Features Support Human and Machine Social Understanding
Xiaoming Liu, Michigan State University, USA
Human Recognition At the Era of Foundation Models
Cathy Mondloch, Brock University, Canada
How Does Variability Influence Face Learning?
Jonathon Phillips, National Institute of Standards and Technology, USA
The Impact of 30+ Years of Face Recognition Competitions (tentative)
Arun Ross, Michigan State University, USA
Explainable Face Recognition Using Foundation Models
Peter Rot, University of Ljubljana, Slovenia
FaceMINT: Gaining Insights into Face Recognition Models Using Mechanistic Interpretability
Walter Scheirer, University of Notre Dame, USA
Escaping the Uncanny Valley of Synthetic Faces
Clare Sutherland, University of Aberdeen, UK
Cross Race Effects In AI Face Detection
Alex Todorov, University of Chicago, USA
The Idiosyncratic Nature of Face Evaluation
Alice Towler, University of Queensland, Australia
Where’s Wally in the Wild: How Well Can Police and Super-recognisers Spot Targets In a Live Crowd?
Galit Yovel, University of Tel Aviv, Israel
Using Deep Learning Algorithms to Disentangle the Contributions of Visual and Semantic Information in Human Perception and Memory
Panelists (tentative)
Mark Nixon, University of Southampton, UK
Jim Haxby, Dartmouth College, USA
Organizers (speakers or panelists)
Kevin Bowyer, University of Notre Dame, USA
Eilidh Noyes - University of Leeds, UK
Alice O'Toole - The University of Texas at Dallas, USA
Face, Body, and Person Identification in Real-world Viewing Conditions
P. Jonathon Phillips, National Institute of Standards and Technology, USA
Walter Scheirer, University of Notre Dame, USA
Poster Presenters
Daniel Albohn, University of Chicago, USA
The Average Person Does Not Exist: The Challenge of Capturing Human Variability with Large Language Models
Kristen Baker, University of Kent, UK
Seen, But Not Recognized: Spontaneous Recognition Depends on Degree of Familiarity, with Little Influence
of Priming
Louisa Conwil, University of Notre Dame, USA
The Impact of Facial Filters on Human and Machine Recognition
Leonard van Dyck, Justis Liebig University, Germany
Mixed Selectivity for Faces and Bodies in Deep Neural Networks and Human Visual Cortex
Katie Gray, University of Reading, UK
Detecting and Discriminating AI-generated Faces
Alysha Hua, University of Adelaide, Australia
Individual Differences in Automation Reliance in a Face Matching Task
Barbora Illithova, University of Aberdeen, UK
Impressions are in the mind of the beholder: Idiosyncratic associations unite domains of naturalistic whole-person perception
Sarah Laurence, Open University, UK
Zoe Little, University of New South Wales, Australia
Confidence Carryover In Face Matching Judgments By Experts and Novices
Leoni Masrouja, University of Aberdeen, UK
Women are perceived as competent, but only in ‘pink’ locations: How gender stereotyped locations affect face impressions
Reuben Moreton, Reli Research, UK
Synthetic Data and Algorithms in Forensic Face Identification
Kira Noad, Justus-Liebig-Universität Gieß, Germany
Conceptual Knowledge Shapes the Neural Representations of Learned Faces in Non-Visual Regions of the Brain
Kay Ritchie, University of Lincoln UK
Face Masks and Fake Masks
Ben Steward, Australian National University, Australia
Flexible Cue Integration in Emotion Perception: Insights from Bayesian Models and Digital Avatars