Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal Information
Dynamic MLP, which is parameterized by the learned embeddings of variable locations and dates to help fine-grained image classification.
Requirements
Experiment Environment
- python 3.6
- pytorch 1.7.1+cu101
- torchvision 0.8.2
Get pretrained models for SK-Res2Net following here.
Get datasets following here.
Train the model
1. Train image-only model
Specify --image_only for training image-only models.
- ResNet-50 (67.924% Top-1 acc)
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python3 train.py
--name res50_image_only
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