162 citations · 303 across the 20 of their papers we have counts for
6 papers · 1 filter
Deep Active Learning with Augmentation-based Consistency Estimation
SeulGi Hong, Heonjin Ha, Junmo Kim +1
In active learning, the focus is mainly on the selection strategy of unlabeled data for enhancing the generalization capability of the next learning cycle. For this, various uncert…
PBP-Net: Point Projection and Back-Projection Network for 3D Point Cloud Segmentation
JuYoung Yang, Chanho Lee, Pyunghwan Ahn +3
Following considerable development in 3D scanning technologies, many studies have recently been proposed with various approaches for 3D vision tasks, including some methods that ut…
Highway Driving Dataset for Semantic Video Segmentation
Byungju Kim, Junho Yim, Junmo Kim
Scene understanding is an essential technique in semantic segmentation. Although there exist several datasets that can be used for semantic segmentation, they are mainly focused on…
Collaborative Method for Incremental Learning on Classification and Generation
Byungju Kim, Jaeyoung Lee, Kyungsu Kim +2
Although well-trained deep neural networks have shown remarkable performance on numerous tasks, they rapidly forget what they have learned as soon as they begin to learn with addit…
Continual Learning with Extended Kronecker-factored Approximate Curvature
Janghyeon Lee, Hyeong Gwon Hong, Donggyu Joo +1
We propose a quadratic penalty method for continual learning of neural networks that contain batch normalization (BN) layers. The Hessian of a loss function represents the curvatur…
Residual Continual Learning
Janghyeon Lee, Donggyu Joo, Hyeong Gwon Hong +1
We propose a novel continual learning method called Residual Continual Learning (ResCL). Our method can prevent the catastrophic forgetting phenomenon in sequential learning of mul…