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Since it was not mentioned in our github, I thought maybe it is useful to say here. If you are using deep neural network depth estimation in KITTI, just one thing to doublecheck:
KITTI raw dataset has many splits and these splits have overlap with each other. It is important that you don't test on the data which was in your training (or mention it in the paper that which sequences was in the training set).
Eigen Split:
00 no
01 yes
02 yes
03 no
04 no
05 no
06 yes
07 no
08 yes
09 yes
10 yes
"yes" means that the odometry sequence is in the training set. You can double check it yourself as well and find the mappings.
There is also another split used by SfMLearner which splits the odometry sequences 00-10 into test and train (I think 00-07 for train and 08-10 for test. see their paper)
What we did was we excluded the odometry sequence 00 -10 from the whole KITTI raw dataset and trained on that. Our pre-trained model will be released in our GitHub soon (hopefully in few days) in case other people want to just use it and evaluate their methods.
Thank you,
Ali
The text was updated successfully, but these errors were encountered:
Do you know where can I find the official source of the relation between eigen split and odometry?
Because I found the statement is inconsistent with D3VO in which they state that
sequences 00, 03, 04, 05, 07 are in the training set of the Eigen split
I found this is important for benchmark comparison in model-based VO.
Thank you!
Hi,
Since it was not mentioned in our github, I thought maybe it is useful to say here. If you are using deep neural network depth estimation in KITTI, just one thing to doublecheck:
KITTI raw dataset has many splits and these splits have overlap with each other. It is important that you don't test on the data which was in your training (or mention it in the paper that which sequences was in the training set).
KITTI Stereo 2015 (know as KITTI split in monodepth paper):
00 yes
01 yes
02 yes
03 no
04 yes
05 yes
06 yes
07 yes
08 yes
09 yes
10 yes
Eigen Split:
00 no
01 yes
02 yes
03 no
04 no
05 no
06 yes
07 no
08 yes
09 yes
10 yes
"yes" means that the odometry sequence is in the training set. You can double check it yourself as well and find the mappings.
There is also another split used by SfMLearner which splits the odometry sequences 00-10 into test and train (I think 00-07 for train and 08-10 for test. see their paper)
What we did was we excluded the odometry sequence 00 -10 from the whole KITTI raw dataset and trained on that. Our pre-trained model will be released in our GitHub soon (hopefully in few days) in case other people want to just use it and evaluate their methods.
Thank you,
Ali
The text was updated successfully, but these errors were encountered: