Rethinking FID Through the Geometry of the Reference Dataset 事件

Rethinking FID Through the Geometry of the Reference Dataset arXiv:2605.29335v1 Announce Type: new Abstract: Fr\'echet Inception Distance (FID) is widely used to evaluate image generators, yet lower FID does not always correspond to better sample quality. We show that this mismatch depends in part on the geometry of the reference dataset. In a controlled study across six datasets, distributional density and effective rank significantly explain how FID changes as sample quality improves. Concent