2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CV2022
Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations
Thomas Verelst, Paul K. Rubenstein, Marcin Eichner +2
As natural images usually contain multiple objects, multi-label image classification is more applicable "in the wild" than single-label classification. However, exhaustively annota…
cs.CV2019★ 2 cited
Generating superpixels using deep image representations
Thomas Verelst, Matthew Blaschko, Maxim Berman
Superpixel algorithms are a common pre-processing step for computer vision algorithms such as segmentation, object tracking and localization. Many superpixel methods only rely on c…