RandLA-Net-pytorch
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squared distances
First of all thanks for sharing you RandLa-Net implementation, it is very helpful. I've noticed that the distances returned by knn() are squared (at least when using torch_points_kernels). In the paper they mention using non-squared distances, and from a quick look at the tensorflow code, it seems they indeed use non-squared distances. Hope this is helpful. Thanks, Amnon Drory
Thanks Amnon for your comment !
Indeed, this could be an important difference that impoverished our results. Did you noticed any improvement in results with the non-squared distance ?
Thibaud
@AmnonDrory , Did you manage to try using un-squared distances? was there an improvement? I've noticed that the torch_point_kernels knn returns automatically squared distances, so I'm wondering if there is any other way fixing this issue rather than just taking the square root of distances. Thanks