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This repository has been archived by the owner on Sep 2, 2024. It is now read-only.
Hi, @ozansener, I find that there may be some mismatch among the depth loss, metric and reported results in the paper. In the depth loss, those pixels with <0 loss are excluded, but in the depth metric, pixels with <250 target depth (normalized by mean and std) are all included, So I think they include all the pixels, maybe this is a bug because 250 should be used for segmentation but not depth regression. Also, in Tab. 4 of your paper w.r.t disparity error, are they the direct output of the depth branch of the model in your code? Thanks.
Hi, @ozansener, I find that there may be some mismatch among the depth loss, metric and reported results in the paper. In the depth loss, those pixels with <0 loss are excluded, but in the depth metric, pixels with <250 target depth (normalized by mean and std) are all included, So I think they include all the pixels, maybe this is a bug because 250 should be used for segmentation but not depth regression. Also, in Tab. 4 of your paper w.r.t disparity error, are they the direct output of the depth branch of the model in your code? Thanks.
PS: For evaluating the depth regression performance, why should the gt and pred be cast as int?https://github.com/intel-isl/MultiObjectiveOptimization/blob/5d8e8343c56cf3184081f71cc4a661af64e7cf7e/multi_task/metrics.py#L46-L54
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