Open YurongYou opened 2 years ago
Follow-up questions for finetuning PointRCNN on Kitti,
Thanks in advance!
@YurongYou For your questions, 1. yes, those are mean across multiple splits. 2. And yes. I use resampled the gt points from the sub sampled pointclouds for the _db_info files. @barzanisar For your questions, 1. I did increase the number of iterations but I think I did not increase it to 1600 epochs for 5%. I tried maybe a bit fewer iterations than that because I found that you don't need those many epochs to get the best performance. 2. I used the adam_onecycle, and for that dropping learning rate, that's the default from OpenPCDet. 3. For that syncBatchNorm, I was following the shuffle batchnorm practice from MocoV2 codebase. So I didn't apply that. There was no particular reason for not using it. You are welcome to try!
Thanks @zaiweizhang for replying. How many epochs did you train for on 5% split?
I think I tried 200 epochs, and the loss converges
Hi! First I would like to thank you for this great work! It is very interesting and I like it a lot! In the meantime, I have two questions about the KITTI fine-tuning experiments:
kitti_dbinfos_train.pkl
, which is generated from the 100% KITTI train set, for augmentation. Should different splits use differentkitti_dbinfos_train.pkl
generated from corresponding splits for augmentation?Thanks in advance!