5 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 5 cited
ConMatch: Semi-Supervised Learning with Confidence-Guided Consistency Regularization
Jiwon Kim, Youngjo Min, Daehwan Kim +4
We present a novel semi-supervised learning framework that intelligently leverages the consistency regularization between the model's predictions from two strongly-augmented views…
cs.CV2022★ 1 cited
Semi-Supervised Learning of Semantic Correspondence with Pseudo-Labels
Jiwon Kim, Kwangrok Ryoo, Junyoung Seo +4
Establishing dense correspondences across semantically similar images remains a challenging task due to the significant intra-class variations and background clutters. Traditionall…
cs.LG2022
AggMatch: Aggregating Pseudo Labels for Semi-Supervised Learning
Jiwon Kim, Kwangrok Ryoo, Gyuseong Lee +5
Semi-supervised learning (SSL) has recently proven to be an effective paradigm for leveraging a huge amount of unlabeled data while mitigating the reliance on large labeled data. C…