HKUST-Aerial-Robotics / Stereo-RCNN

Code for 'Stereo R-CNN based 3D Object Detection for Autonomous Driving' (CVPR 2019)

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About the unstable performance

tjulyz opened this issue · comments

commented

Hi,
Thanks for your kind share. When I try to run the train step several times to get several models, I found that the performance are unstable. Sometimes, the AP3D for hardset may degrade by 3%. I have got results (~51.1, ~34.5, ~30.1 for easy, moderate, hard). Could you please help me?
Thanks a lot!

Hi, it is the best model you trained or the worst model?

commented

Usually, ~1% variance should be normal due to the random property. But I didn't see such a different AP. Please make sure using the exact parameters as we provide.

commented
commented

Hi, I have another question about the test set performance. Did you directly test the model which is trained on training set(3000+images) and reported the test set(7500+images) performance? Have you merged the training set and validation set to retrain the model when evaluated on the test set?
Thanks a lot!