Multi-Modal Methods
EmbraceNet: A robust deep learning architecture for multimodal classification
Introduced by Choi et al. in EmbraceNet: A robust deep learning architecture for multimodal classificationPapers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Classification | 2 | 20.00% |
| Emotion Recognition | 1 | 10.00% |
| Image Generation | 1 | 10.00% |
| Image-text Classification | 1 | 10.00% |
| Multilingual Image-Text Classification | 1 | 10.00% |
| Text Classification | 1 | 10.00% |
| Activity Recognition | 1 | 10.00% |
| Human Activity Recognition | 1 | 10.00% |
| General Classification | 1 | 10.00% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
