Background-Free Objectness Learning for Class-Agnostic Detection
Object detectors are typically trained under closed-set supervision, where unlabeled regions are implicitly treated as background. Under incomplete annotations, this assumption introduces objectness bias: visually valid but unlabeled objects are used as negatives, tying objectness to the annotated taxonomy rather than...
Dania Batool, Liliana Lo Presti, M. La Cascia et al.
· 0 citations