Computer Graphics from a Neuroscientist’s Perspective

Authors: Shreya Kapoor, Bernhard Egger

Published in: Second Workshop on Representational Alignment (Re-Align) at ICLR 2025, Singapore.

Abstract

A hallmark of human vision is to recognize objects in complex naturalistic scenes. However, the exact mechanism behind the representations of a three-dimensional scene remains obscure. This study proposes a tool to investigate human perception by using a computer graphics approach. We use three-dimensional object meshes to render synthetic scenes and try to study how these scenes will be represented in the brain. We render a collection of datasets with different appearance and pose variations by changing exactly one property at a time. A model is trained on each of these datasets for a classification task and is then evaluated using alignment metrics; deviations in metrics such as Centered Kernel Alignment (CKA) and Representational Similarity Analysis (RSA) indicate the importance of a particular brain region in representing a particular property. In conclusion, we propose a promising method to study the brain using computer graphics to provide valuable insights into human vision.