39 citations · 159 across the 37 of their papers we have counts for
3 papers · 1 filter
ACLS: Adaptive and Conditional Label Smoothing for Network Calibration
Hyekang Park, Jongyoun Noh, Youngmin Oh +2
We address the problem of network calibration adjusting miscalibrated confidences of deep neural networks. Many approaches to network calibration adopt a regularization-based metho…
RankMixup: Ranking-Based Mixup Training for Network Calibration
Jongyoun Noh, Hyekang Park, Junghyup Lee +1
Network calibration aims to accurately estimate the level of confidences, which is particularly important for employing deep neural networks in real-world systems. Recent approache…
Camera-Driven Representation Learning for Unsupervised Domain Adaptive Person Re-identification
Geon Lee, Sanghoon Lee, Dohyung Kim +3
We present a novel unsupervised domain adaption method for person re-identification (reID) that generalizes a model trained on a labeled source domain to an unlabeled target domain…