FGVC12 will explore topics of broad interest to the computer vision community, specifically addressing self-supervision, limited data, and human-in-the-loop learning through the challenging lens of fine-grained learning. This focus extends beyond traditional computer vision, offering methodologies applicable to real-world scenarios in domains like ecology, biology, medicine, and art history, thus fostering participation from researchers outside the CVPR community. The workshop will feature innovative challenges, building upon successful past competitions like iNaturalist, which have previously introduced new datasets and fostered novel solutions. FGVC12 will feature not only leading researchers from the field of computer vision, but also experts from domains such as biomedical data science and ecology to promote discussion of open problems in these disciplines.