ISIM: Iterative Self-Improved Model for Weakly Supervised Segmentation. (arXiv:2211.12455v2 [cs.CV] UPDATED)

Weakly Supervised Semantic Segmentation (WSSS) is a challenging task aiming
to learn the segmentation labels from class-level labels. In the literature,
exploiting the information obtained from Class Activation Maps (CAMs) is widely
used for WSSS studies. However, as CAMs are obtained from a classification
network, they are interested in the most discriminative parts of the objects,
producing non-complete prior information for segmentation tasks. In this study,
to obtain more coherent CAMs with segmentation labels, we propose a framework
that employs …

arxiv iterative segmentation