5 citations · 6 across the 2 of their papers we have counts for
4 papers
Few-shot Metric Learning: Online Adaptation of Embedding for Retrieval
Deunsol Jung, Dahyun Kang, Suha Kwak +1
Metric learning aims to build a distance metric typically by learning an effective embedding function that maps similar objects into nearby points in its embedding space. Despite r…
Integrative Few-Shot Learning for Classification and Segmentation
Dahyun Kang, Minsu Cho
We introduce the integrative task of few-shot classification and segmentation (FS-CS) that aims to both classify and segment target objects in a query image when the target classes…
Relational Embedding for Few-Shot Classification
Dahyun Kang, Heeseung Kwon, Juhong Min +1
We propose to address the problem of few-shot classification by meta-learning "what to observe" and "where to attend" in a relational perspective. Our method leverages relational p…
Hypercorrelation Squeeze for Few-Shot Segmentation
Juhong Min, Dahyun Kang, Minsu Cho
Few-shot semantic segmentation aims at learning to segment a target object from a query image using only a few annotated support images of the target class. This challenging task r…