11 citations · 17 across the 23 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.CV2023
Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI
Qinqian Lei, Bo Wang, Robby T. Tan
Detecting human-object interactions (HOI) in a few-shot setting remains a challenge. Existing meta-learning methods struggle to extract representative features for classification d…
cs.CE2023★ 1 cited
ChiMera: Learning with noisy labels by contrasting mixed-up augmentations
Zixuan Liu, Xin Zhang, Junjun He +5
Learning with noisy labels has been studied to address incorrect label annotations in real-world applications. In this paper, we present ChiMera, a two-stage learning-from-noisy-la…