about the preprocessed NYU Depth V2 about sparse-to-dense.pytorch HOT 6 CLOSED

The pre-processed dataset simply registers the depth frame with the rgb frame, and there is no augmentation. The data augmentation is done on the fly during training. See below:

There are 47584 frames in the training set.

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Thanks

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Hi, @fangchangma Thanks for sharing the code. About the nyu dataset, have the depth images been filled and which method was used, cross-bilateral filter or Colorization? Thank you.

Edit: I checked the paper and it says cross-bilateral filter. No need to respond. Thanks.

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@icemiliang

About the nyu dataset, have the depth images been filled

No, there is no need for pre-processing of depth.

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@fangchangma It says in the paper section IV-A that the ground truth depth images were in-painted with a cross-bilateral filter after projected to the RGB images. This is what I meant. Please let me know if I understand it correctly.

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@icemiliang @fangchangma @Ariel-JUAN @timethy @abdo-eldesokey Hi, How can I down the dataset quickly? It's so low speed when I use wget http://datasets.lids.mit.edu/sparse-to-dense/data/kitti.tar.gz.

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