SCOPE 

Face recognition has been a topic of intense scientific research for over a half century and has in recent years been studied both by psychologists and computer vision/machine learning researchers. As the field of face recognition has matured, researchers have begun to look more broadly at the problem of person recognition. Deep learning models, inspired by the primate visual system, underlie much of the progress made in computationally grounded solutions to these problems. The goal of this small, focused workshop is to discuss and take stock of the many rapid advances in the field including deep learning models, generative AI, progress in expanding on face recognition to include bodies and people in real-world environments. This workshop will bring together face, body, and person recognition experts with the goal of advancing the field through a platform of shared knowledge and interdisciplinary exchange. Understanding how deep-network-based computational strategies of face, body, and person recognition relate to human perception is critical to appropriate applications of this technology in the public sphere. We will also consider how deep networks have changed the way we think about person recognition, by offering new tools and techniques for synthesizing and altering faces in predictable ways. Despite the fast rate of progress on these issues, there are many unanswered questions. Progress at this rate requires us to think "out-of-the-box" in linking human and neural processes to effective computational solutions. We do not know whether/how the underlying representations and computational strategies used by deep networks relate to human face, body, and person processing. As we go forward, consideration and discussion of the following topics can motivate and focus the coming decade of research. Topics to be discussed at the workshop: 

• Merging face and body identification and perception for unconstrained images

• The foundations of modeling face, body, and person recognition in humans

• Synthetic faces and generative AI: theory, detection, and training sets

In this workshop, we will bring together face, body, and person recognition researchers from psychology, cognitive neuroscience, and computer vision.  We will discuss these questions through presentations, panels, and posters. This workshop will allow the community to assess the current state of the art in machine learning, and will help to chart a path for future research. Workshop attendance will be limited to a small number of participants to allow for active participation by all. 

Workshop location. The location will be Notre Dame's London Global Gateway Building, Fischer Hall, located at Trafalgar Square.  1-4 Suffolk Street, London, SW1Y 4HG. Venue