Evaluating on part segument results about pointnet

[charlesq34]

Thanks @eriche2016 for your questions

I'll leave (1) to Kaichun @daerduoCarey
As to (2) evaluation should be on the original sets of points which do have variable numbers. We can set a MAX_NUM_POINT and use that for evaluation and if there are less than those points we can replicate existing points (won't affect max pooled result) and only look at predictions at the first N valid points

@daerduoCarey could you also comment on them?

[daerduoCarey]

Hi @eriche2016 ,

For question (1), we assume that we know the object category for the object that we are segmenting. So, we only allow the prediction to be the semantic labels that belong to the known object class. For example, for a given chair, we only allow the network to predict "chair legs", "chair seats", etc. and disable it to predict "table legs" and "airplane wings", etc. So when calculating IoU, we are using cur_gt_label to select out the semantic labels that are allowed to predict. We mentioned this point in the paper page 10 Appendix C PointNet Segmentation Network third paragraph.

Hope this answer your question, thank you!

[eriche2016]

Thank you very much for your quick answer. It is clear to me now.