517 citations · 727 across the 47 of their papers we have counts for
15 papers · 1 filter
Learning to Detect Semantic Boundaries with Image-level Class Labels
Namyup Kim, Sehyun Hwang, Suha Kwak
This paper presents the first attempt to learn semantic boundary detection using image-level class labels as supervision. Our method starts by estimating coarse areas of object cla…
HIER: Metric Learning Beyond Class Labels via Hierarchical Regularization
Sungyeon Kim, Boseung Jeong, Suha Kwak
Supervision for metric learning has long been given in the form of equivalence between human-labeled classes. Although this type of supervision has been a basis of metric learning…
Cross-Domain Ensemble Distillation for Domain Generalization
Kyungmoon Lee, Sungyeon Kim, Suha Kwak
Domain generalization is the task of learning models that generalize to unseen target domains. We propose a simple yet effective method for domain generalization, named cross-domai…
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…
Improving Cross-Modal Retrieval with Set of Diverse Embeddings
Dongwon Kim, Namyup Kim, Suha Kwak
Cross-modal retrieval across image and text modalities is a challenging task due to its inherent ambiguity: An image often exhibits various situations, and a caption can be coupled…
Combating Label Distribution Shift for Active Domain Adaptation
Sehyun Hwang, Sohyun Lee, Sungyeon Kim +2
We consider the problem of active domain adaptation (ADA) to unlabeled target data, of which subset is actively selected and labeled given a budget constraint. Inspired by recent a…