PLMCL: Partial-Label Momentum Curriculum Learning for Multi-Label Image Classification. (arXiv:2208.09999v1 [cs.CV])

Multi-label image classification aims to predict all possible labels in an
image. It is usually formulated as a partial-label learning problem, given the
fact that it could be expensive in practice to annotate all labels in every
training image. Existing works on partial-label learning focus on the case
where each training image is annotated with only a subset of its labels. A
special case is to annotate only one positive label in each training image. To
further relieve the annotation …

arxiv classification curriculum curriculum learning cv image learning