Hi there,
First of all, thank you for this incredible research and for sharing the code.
I am currently testing your network, but I've encountered an issue where the performance on ShapeNet55 partial inputs is lower than expected.
Here are the details of my environment:
Script used: tools/inference.py (provided in the repository)
Weights: Pre-trained c55 weights (ShapeNet55-34)
Dataset: Prepared exactly as described in the DATASET.md (unzipped and renamed folders accordingly)
Despite following the instructions, the reconstruction results seem a bit off/unstable. Could you provide some insight into what might be causing this? For instance, are there any specific preprocessing steps or scale-related issues I should double-check?
Attached files are mug and chair.
But, additionally airplane was fine.
Is it the problem caused by the number of datasets?
Thank you for your help!
Hi there,
First of all, thank you for this incredible research and for sharing the code.
I am currently testing your network, but I've encountered an issue where the performance on ShapeNet55 partial inputs is lower than expected.
Here are the details of my environment:
Script used: tools/inference.py (provided in the repository)
Weights: Pre-trained c55 weights (ShapeNet55-34)
Dataset: Prepared exactly as described in the DATASET.md (unzipped and renamed folders accordingly)
Despite following the instructions, the reconstruction results seem a bit off/unstable. Could you provide some insight into what might be causing this? For instance, are there any specific preprocessing steps or scale-related issues I should double-check?
Attached files are mug and chair.
But, additionally airplane was fine.
Is it the problem caused by the number of datasets?
Thank you for your help!