12 citations · 43 across the 12 of their papers we have counts for
4 papers · 1 filter
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-Refinement
Beomyoung Kim, Youngjoon Yoo, Chaeeun Rhee +1
Weakly-supervised instance segmentation (WSIS) has been considered as a more challenging task than weakly-supervised semantic segmentation (WSSS). Compared to WSSS, WSIS requires i…
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning
Sungmin Cha, Beomyoung Kim, Youngjoon Yoo +1
This paper introduces a solid state-of-the-art baseline for a class-incremental semantic segmentation (CISS) problem. While the recent CISS algorithms utilize variants of the knowl…
Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation
Beomyoung Kim, Sangeun Han, Junmo Kim
Weakly-supervised semantic segmentation (WSSS) using image-level labels has recently attracted much attention for reducing annotation costs. Existing WSSS methods utilize localizat…
TricubeNet: 2D Kernel-Based Object Representation for Weakly-Occluded Oriented Object Detection
Beomyoung Kim, Janghyeon Lee, Sihaeng Lee +2
We present a novel approach for oriented object detection, named TricubeNet, which localizes oriented objects using visual cues ( heatmap) instead of oriented box offsets re…