Methods › Computer Vision › Feature Pyramid Blocks
Feature Pyramid Blocks
The archive attaches this collection's text per method and the copies differ: 2 distinct texts across 10 of the 10 methods here. All are shown, most-carried first (a tie goes to the text carrying Papers with Code's collection boilerplate, then to the longer text); no vote is taken between them.
Text 1, carried by 6 of 10 methods:
Feature Pyramid Blocks are a basic component in recognition systems for detecting objects at different scales.
Text 2, carried by 4 of 10 methods:
Feature Extractors for object detection are modules used to construct features that can be used for detecting objects. They address issues such as the need to detect multiple-sized objects in an image (and the need to have representations that are suitable for the different scales).
Methods
All 10 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.
| PAFPN | – | 124 |
| BiFPN | – | 48 |
| Attention Pooling | – | 46 |
| NAS-FPN | – | 11 |
| RFP Recursive Feature Pyramid | – | 10 |
| Balanced Feature Pyramid | – | 7 |
| FPG Feature Pyramid Grid | – | 5 |
| MLFPN | – | 2 |
| ASFF Adaptively Spatial Feature Fusion | – | 1 |
| Exact Fusion Model | – | 1 |