Speakers
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
Peter Hancock, Stirling University, Scotland (tentative)
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
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
Clare Sutherland, University of Aberdeen, UK
Alex Todorov, University of Chicago, USA
Alice Towler, University of Queensland, USA
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
Kristen Baker, University of Kent, UK
Seen, but not recognized: Spontaneous recognition depends on degree of familiarity, with little influence of priming
Leonard van Dyck, Justis Liebig University, Germany
Mixed selectivity for faces and bodies in deep neural networks and human visual cortex
Alysha Hua, University of Adelaide, Australia
Individual Differences in Automation Reliance in a Face Matching Task
Katie Gray, University of Reading, UK
Reuben Moreton, Reli Research, UK
Synthetic data and algorithms in forensic face identification
Kay Ritchie, University of Lincoln UK
Ben Steward, Australian National University, Australia.
Flexible Cue Integration in Emotion Perception: Insights from Bayesian Models and Digital Avatars