Methods › Computer Vision › Image Feature Extractors

Image Feature Extractors

4 methods 191 papers tagged archive 2025-07-28

Image Feature Extractors are functions or modules that can be used to learn representations from images. The most common type of feature extractor is a convolution where a kernel slides over the image, allowing for parameter sharing and translation invariance. Below you can find a continuously updating list of image feature extractors.

Methods

All 4 methods in this collection, most-tagged first. Year is the archive's introduced_year; the archive stores 2000 when it has none, shown here as “–”. Papers counts distinct papers the archive tags with the method. Click a heading to sort.

Non-Local Operation – 181
Involution – 5
Local Relation Layer – 3
Hamburger – 2