3 citations · 10 across the 12 of their papers we have counts for
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cs.CV2023
What, How, and When Should Object Detectors Update in Continually Changing Test Domains?
Jayeon Yoo, Dongkwan Lee, Inseop Chung +2
It is a well-known fact that the performance of deep learning models deteriorates when they encounter a distribution shift at test time. Test-time adaptation (TTA) algorithms have…
cs.CV2023
ProxyDet: Synthesizing Proxy Novel Classes via Classwise Mixup for Open-Vocabulary Object Detection
Joonhyun Jeong, Geondo Park, Jayeon Yoo +2
Open-vocabulary object detection (OVOD) aims to recognize novel objects whose categories are not included in the training set. In order to classify these unseen classes during trai…
cs.LG2023★ 2 cited
SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
JunHoo Lee, Jayeon Yoo, Nojun Kwak
In this paper, we hypothesize that gradient-based meta-learning (GBML) implicitly suppresses the Hessian along the optimization trajectory in the inner loop. Based on this hypothes…