Fine-grained categorization, the precise differentiation between similar plant or animal species, disease of the retina, architectural styles, etc., is an extremely challenging problem, pushing the limits of both human and machine ability. In these domains expert knowledge is typically required, and the question that must be addressed is how can we develop systems that can efficiently discriminate between large numbers of highly similar visual concepts. The 10th Workshop on Fine-Grained Visual Categorization (FGVC10) explores topics related to supervised learning, self- supervised learning, semi-supervised learning, matching, localization, domain adaptation, transfer learning, few-shot learning, machine teaching, multimodal learning (e.g., audio and video), 3D- vision, crowd-sourcing, image captioning and generation, out-of- distribution detection, open-set recognition, human-in-the-loop learning, etc., all through the lens of fine-grained understanding. Topics relevant for FGVC10 are neither restricted to vision nor categorization. FGVC10 consists of invited talks from world- renowned computer vision experts and domain experts (e.g., art), poster sessions, challenges, and peer-reviewed extended abstracts. To mark FGVC’s 10th anniversary, we have confirmed five panellists for a discussion of the history and future of FGVC. We aim to stimulate debate and to expose the wider computer vision community to new challenging problems which have the potential for large societal impact but do not traditionally receive a significant amount of exposure at other CVPR workshops.