Image Models
MetaFormer
Introduced by Yu et al. in MetaFormer Is Actually What You Need for VisionMetaFormer is a general architecture abstracted from Transformers by not specifying the token mixer.
Source: MetaFormer Is Actually What You Need for Vision
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Image Classification | 8 | 16.67% |
| Semantic Segmentation | 8 | 16.67% |
| Object Detection | 6 | 12.50% |
| Image Segmentation | 3 | 6.25% |
| Medical Image Segmentation | 3 | 6.25% |
| Specificity | 2 | 4.17% |
| Decoder | 2 | 4.17% |
| Autonomous Driving | 1 | 2.08% |
| Object | 1 | 2.08% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
