NVlabs / AL-MDN

Official pytorch implementation of Active Learning for deep object detection via probabilistic modeling (ICCV 2021)
https://openaccess.thecvf.com/content/ICCV2021/html/Choi_Active_Learning_for_Deep_Object_Detection_via_Probabilistic_Modeling_ICCV_2021_paper.html
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diverges during training on my own dataset #22

Open hbhflw2000 opened 1 year ago

hbhflw2000 commented 1 year ago

Hello,

I succeeded in reproducing your results on your dataset. However, when it comes to my own traffic light dataset, which contains many small objects, the localization heads starts to diverge. I tried my best to turn down learning rate to 1e-7 or less, The classification head converges, and works at test sets; But the localization head diverges at loss=5 for four localizers (loss =NAN after that), and predict nonsense at test sets.

Any suggestions? Thanks in advacne

AliceShynie commented 1 year ago

Did you manage to solve this?