This week I am working on reimplementing experiments in the field of fine-grained visual classification.The data set used for this study is CUB-200-2011, a fine-grained bird classification dataset.
Summary
Method | Top-1 Accuracy - My Result | Top-1 Accuracy - Original Result | Code |
---|---|---|---|
FFVT | 91.62 | 91.6 | link |
Vit-NeT | 91.6 | 91.7 | link |
TransFG | NA | 91.7 | link |
IELT | 91.267 | 91.8 | link |
SAC | NA | 91.8 | link |
HERBS | 93.01 | 93.1 | link |
Details
- FFVT
- IELT
- Vit-Net
- HERBS
- TransFG: Due to GPU limitations, the training steps were not completed. However, I successfully migrated the workflow to Google Colab and optimized the data loading steps, reducing the time from 40 minutes to 2 minutes.
- SAC: Learned how to set up a virtual environment to incorporate TensorFlow 1.45 and Python 3.7, but encountered issues on a MacBook due to hardware limitations.