162 citations · 303 across the 20 of their papers we have counts for
5 papers · 1 filter
Self-Supervised Knowledge Transfer via Loosely Supervised Auxiliary Tasks
Seungbum Hong, Jihun Yoon, Junmo Kim +1
Knowledge transfer using convolutional neural networks (CNNs) can help efficiently train a CNN with fewer parameters or maximize the generalization performance under limited superv…
Joint Negative and Positive Learning for Noisy Labels
Youngdong Kim, Juseung Yun, Hyounguk Shon +1
Training of Convolutional Neural Networks (CNNs) with data with noisy labels is known to be a challenge. Based on the fact that directly providing the label to the data (Positive L…
Extending Contrastive Learning to Unsupervised Coreset Selection
Jeongwoo Ju, Heechul Jung, Yoonju Oh +1
Self-supervised contrastive learning offers a means of learning informative features from a pool of unlabeled data. In this paper, we delve into another useful approach -- providin…
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…