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KD

This repository implements Knowledge Distillation in the SimpleDet framework.

Qucik Start

python3 detection_train.py --config config/kd/retina_r50v1b_fpn_1x_fitnet_g10.py
python3 detection_test.py --config config/kd/retina_r50v1b_fpn_1x_fitnet_g10.py

Results and Models

All AP results are reported on the minival2014 split of the COCO dataset.

Model Backbone Head Train Schedule AP AP50 AP75 APs APm APl
Retina R50v1b-FPN 4Conv 1X 36.6 56.9 39.0 20.3 40.7 47.2
Retina R50v1b-FPN-TR152v1b1X 4Conv 1X 38.9 59.0 41.6 21.4 43.3 52.1
Retina R50v1b-FPN-TR152v1b1X 4Conv 2X 40.1 60.6 43.1 21.8 44.5 54.3
Faster R50v1b-FPN 2MLP 1X 37.2 59.4 40.4 22.3 41.3 47.6
Faster R50v1b-FPN 2MLP 2X 38.0 59.7 41.5 22.2 41.6 48.8
Faster R50v1b-FPN-TR152v1b2X 2MLP 1X 39.9 61.3 43.6 22.7 44.2 52.7
Faster R50v1b-FPN-TR152v1b2X 2MLP 2X 40.5 62.2 43.9 23.1 44.7 53.9