CoCoG: Controllable Visual Stimuli Generation based on Human Concept Representations

arXiv:2404.16482v1 Announce Type: cross
Abstract: A central question for cognitive science is to understand how humans process visual objects, i.e, to uncover human low-dimensional concept representation space from high-dimensional visual stimuli. Generating visual stimuli with controlling concepts is the key. However, there are currently no generative models in AI to solve this problem. Here, we present the Concept based Controllable Generation (CoCoG) framework. CoCoG consists of two components, a simple yet efficient AI agent for extracting interpretable concept and predicting …

arxiv concept cs.cv cs.hc human q-bio.nc type visual