Object Detection Models
Stand-Alone Self Attention
Introduced by Ramachandran et al. in Stand-Alone Self-Attention in Vision ModelsStand-Alone Self Attention (SASA) replaces all instances of spatial convolution with a form of self-attention applied to ResNet producing a fully, stand-alone self-attentional model.
Source: Stand-Alone Self-Attention in Vision Models
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Object Detection | 2 | 33.33% |
| 3D Object Detection | 1 | 16.67% |
| Face Anti-Spoofing | 1 | 16.67% |
| Face Recognition | 1 | 16.67% |
| Style Transfer | 1 | 16.67% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
