14 citations · 17 across the 8 of their papers we have counts for
4 papers · 1 filter
DarSwin: Distortion Aware Radial Swin Transformer
Akshaya Athwale, Arman Afrasiyabi, Justin Lagüe +3
Wide-angle lenses are commonly used in perception tasks requiring a large field of view. Unfortunately, these lenses produce significant distortions, making conventional models tha…
Matching Feature Sets for Few-Shot Image Classification
Arman Afrasiyabi, Hugo Larochelle, Jean-François Lalonde +1
In image classification, it is common practice to train deep networks to extract a single feature vector per input image. Few-shot classification methods also mostly follow this tr…
Mixture-based Feature Space Learning for Few-shot Image Classification
Arman Afrasiyabi, Jean-François Lalonde, Christian Gagné
We introduce Mixture-based Feature Space Learning (MixtFSL) for obtaining a rich and robust feature representation in the context of few-shot image classification. Previous works h…
Associative Alignment for Few-shot Image Classification
Arman Afrasiyabi, Jean-François Lalonde, Christian Gagné
Few-shot image classification aims at training a model from only a few examples for each of the "novel" classes. This paper proposes the idea of associative alignment for leveragin…