Image Data Augmentation
Adaptive Pseudo Augmentation
Introduced by Jiang et al. in Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Language Modeling | 2 | 6.45% |
| Language Modelling | 2 | 6.45% |
| Clustering | 2 | 6.45% |
| Chatbot | 1 | 3.23% |
| Fairness | 1 | 3.23% |
| imbalanced classification | 1 | 3.23% |
| Instance Segmentation | 1 | 3.23% |
| Long-tail Learning | 1 | 3.23% |
| Question Answering | 1 | 3.23% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
