KD

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