Finding Task-Relevant Features for Few-Shot Learning by Category Traversal

• Published in: Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 1 - 10
• Main Authors: Li, Hongyang, Eigen, David, Dodge, Samuel, Zeiler, Matthew, Wang, Xiaogang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2019
• Subjects: Benchmark testing; Computer vision; Deep Learning; Feature extraction; Few shot learning; Hands; Pattern recognition; Pragmatics; Training

Few-shot learning is an important area of research. Conceptually, humans are readily able to understand new concepts given just a few examples, while in more pragmatic terms, limited-example training situations are common practice. Recent effective approaches to few-shot learning employ a metric-lea...