← Search

Kwangrok Ryoo

2 accepted papers

2022

ConMatch: Semi-Supervised Learning with Confidence-Guided Consistency Regularization

ECCV 2022poster

"We present a novel semi-supervised learning framework that intelligently leverages the consistency regularization between the model’s predictions from two strongly-augmented views of an image, weighted by a confidence of pseudo-label, dubbed ConMatch. While the latest semi-supervised learning metho…

2022

Semi-Supervised Learning of Semantic Correspondence With Pseudo-Labels

CVPR 2022poster

Establishing dense correspondences across semantically similar images remains a challenging task due to the significant intra-class variations and background clutters. Traditionally, a supervised loss was used for training the matching networks, which requires tremendous manually-labeled data, while…

Cited by 21PDFScholar