2 papers
cs.CV2021
Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency
Aditya Ganeshan, Alexis Vallet, Yasunori Kudo +5
Deep learning models for semantic segmentation rely on expensive, large-scale, manually annotated datasets. Labelling is a tedious process that can take hours per image. Automatica…
cs.CV2021
Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation
Tommi Kerola, Jie Li, Atsushi Kanehira +3
Panoptic segmentation brings together two separate tasks: instance and semantic segmentation. Although they are related, unifying them faces an apparent paradox: how to learn simul…