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lliuz / ARFlow

The official PyTorch implementation of the paper "Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation".

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KIITI datasets used for training and finetuning

RokiaAbdeen opened this issue · comments

commented

I downloaded the following files :
Kitti raw , data_stereo_flow for kitti 2012 , data_scene_flow for kitti 2015
and data_stereo_flow_multiview , data_scene_flow_multiview
first I want to train the model with kittiraw and validate using kitti stereo and kitti scene but I got data assertion error , I thinks that's because may be there is wrong dataset used
could you explain please "according to your config files " what should be the files specified for the pretraining and finetuning if I want to pretrain with kitti raw and fine tune with multiview as you explained in your paper

thanks in advance ..

commented

how did you finetune by multi-view dataset ? in finetuning you specified kitti15 as the training root not multiview file, so the training data here is same to the validation data , that's not same to paper , could you explain this point for me please
when I tried to use multiview dataset for filetuning I got data assertion error because there is no flow_occ folder in multiview dataset
thanks in advance ..