1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2024
Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation
Jihwan Kwak, Sungmin Cha, Taesup Moon
This paper addresses the unrealistic aspect of the commonly adopted Continuous Incremental Semantic Segmentation (CISS) scenario, termed overlapped. We point out that overlapped al…
cs.LG2022★ 1 cited
Towards Diverse Evaluation of Class Incremental Learning: A Representation Learning Perspective
Sungmin Cha, Jihwan Kwak, Dongsub Shim +4
Class incremental learning (CIL) algorithms aim to continually learn new object classes from incrementally arriving data while not forgetting past learned classes. The common evalu…
cs.CV2020
SS-IL: Separated Softmax for Incremental Learning
Hongjoon Ahn, Jihwan Kwak, Subin Lim +3
We consider class incremental learning (CIL) problem, in which a learning agent continuously learns new classes from incrementally arriving training data batches and aims to predic…