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microsoft / MaskFlownet

[CVPR 2020, Oral] MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask

Home Page:https://arxiv.org/abs/2003.10955

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How to do post-processing when submit flow results to KITTI eval server?

chengrongliang opened this issue · comments

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Hi, @simon1727 I noticed you mentioned that force to make ground truth dense in training stage #5.
Then how to do post-process when we submit to Kitti eval server in prediction stage?
In other words, how to get sparse result according to dense flow results, which makes sure getting promising eval results? Because the ground truth is sparse in test dataset also.