Few-shot Learning with a Universal Template (FLUTE)
Pattern for Efficient Learning: A training method for few-shot learning in computer vision.
Getting high accuracy out of a classifier trained on a small number of examples is tricky. You might train the model on several large-scale datasets prior to few-shot training, but what if the few-shot dataset includes novel classes? A new method performs well even in that case.