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autonomousvision / occupancy_networks

This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"
https://avg.is.tuebingen.mpg.de/publications/occupancy-networks
MIT License
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Evaluation issues #89

Closed xianyongqin closed 3 years ago

xianyongqin commented 3 years ago

Thanks for releasing the amazing codes. I have two questions regarding the evaluation.

  1. Your evaluation code seems to only consider one image (000.jpg) from each test model, although there are 20 rendered images per model. Is it the standard evaluation protocol or it does not make any difference when considering all images?

  2. After running eval_meshes.py on your pretrained model, I got a much lower Chamfer distance (0.02) than reported in the paper (0.21). Is this due to the scaling factor (during the preprocessing step, points are scaled into (-0.5, 0.5)) of the point cloud? Moreover, in the Table 1 of the paper, you reported "Chamfer-L1", but actually your codes are computing the L2 distance. Can you please clarify?

xianyongqin commented 3 years ago

This has been addressed in a closed issue #61