Methods › Computer Vision › Instance Segmentation Models
Instance Segmentation Models
The archive attaches this collection's text per method and the copies differ: 3 distinct texts across 15 of the 15 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 12 of 15 methods:
Instance Segmentation models are models that perform the task of Instance Segmentation.
Text 2, carried by 2 of 15 methods:
Object Detection Models are architectures used to perform the task of object detection. Below you can find a continuously updating list of object detection models.
Text 3, carried by 1 of 15 methods:
Semantic Segmentation Models are a class of methods that address the task of semantically segmenting an image into different object classes. Below you can find a continuously updating list of semantic segmentation models.
Methods
All 15 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.
| Mask R-CNN | – | 420 |
| HTC Hybrid Task Cascade | – | 46 |
| Cascade Mask R-CNN | – | 23 |
| PANet | – | 18 |
| CPN Contour Proposal Network | – | 14 |
| GCNet | – | 11 |
| K-Net | – | 6 |
| SCNet | – | 6 |
| CondInst Conditional Convolutions for Instance Segmentation | – | 5 |
| CenterMask | – | 4 |
| VisTR | – | 3 |
| BlendMask | – | 2 |
| AffCorrs Affordance Correspondence | – | 1 |
| Deep-MAC | – | 1 |
| Mask Scoring R-CNN | – | 1 |