Fine categorization, i.e., the fine distinction into species of animals and plants, of car and motorcycle models, of architectural styles, etc., is one of the most interesting and useful open problems that the machine vision community is just beginning to address. Aspects of fine categorization (called 'subordinate categorization' in the psychology literature) are discrimination of related categories, taxonomization, and discriminative vs. generative learning.
Fine categorization lies in the continuum between basic level categorization (object recognition) and identification of individuals (face recognition, biometrics). The visual distinctions between similar categories are often quite subtle and therefore difficult to address with today’s general-purpose object recognition machinery. It is likely that radical re-thinking of some of the matching and learning algorithms and models that are currently used for visual recognition will be needed to approach fine categorization.
This workshop will explore computational questions of modeling, learning, detection and localization. It is our hope that the invited talks, including researchers from psychology and psychophysics, will shed light on human expertise and human performance in subordinate categorization and taxonomization.
For additional details, please see the FGVC4 workshop held in 2017.