Will you provide the code for training and testing on the MVP dataset?

Welcome update to OpenMMLab 2.0

I am Vansin, the technical operator of OpenMMLab. In September of last year, we announced the release of OpenMMLab 2.0 at the World Artificial Intelligence Conference in Shanghai. We invite you to upgrade your algorithm library to OpenMMLab 2.0 using MMEngine, which can be used for both research and commercial purposes. If you have any questions, please feel free to join us on the OpenMMLab Discord at https://discord.gg/amFNsyUBvm or add me on WeChat (van-sin) and I will invite you to the OpenMMLab WeChat group.

Here are the OpenMMLab 2.0 repos branches:

Attention: please create a new virtual environment for OpenMMLab 2.0.

Hi, thanks for your great work!

I am curious about the dimension of your finally generated point descriptors. It seems it is not mentioned in your arxiv paper.

Hi again,
I am getting the AssertionError: assert torch.all(torch.det(R)>0) (reference image above). This was while training for the 3 different configurations in the cfgs folder and for the provided ModelNet datasets.

Removing the assert statement and training it might not give the desired results. Could you please advice what can be done in this case?

Also is any data pre-processing required?

Many thanks in advance.

你好，我看到了test.py，但只得到了模型输出，并没有得出模型指标数据。请问评测代码能开源吗

Hi,

Thank you for making this great work public!

I want to do a fast test on my own objects. Can you provide you trained models on your dataset?

Your work looks great. Would you like open your code to
communication？

Hi Liang,

I notice the testing data on ModelNet is already preprocessed, so I am wondering how do you generate them. Is it generated using the same code as the training data with the seed fixed? That is to say, the same 1024 points are sampled first, and cropped to different point clouds and transformed separately.

As far as I know, sampling different 1024 points for the source and target point clouds can significantly affect the performance, which is the original implementation in RPM-Net. How does GMCNet perform in this setting?

Thanks,
Zheng

cannot import name 'MVP_RG' from 'dataset'

Hi, thanks for the great work!

I am working on a project where I have to register pointclouds of shapenet objects (Complete point cloud) with point clouds generated for a single view of the same object. Was wondering if this code base can be used to do the same?

I was also wondering how the data was prepared, if you have any codes for the same.

Thanks!

svd_cpu: the updating process of SBDSDC did not converge (error: 2)

Hi, Thank you for the nice work.

Though I did install mm3d_pn2 as mentioned in the installation section, I am facing the error, "NameError: name 'furthest_point_sample' is not defined
Segmentation fault (core dumped)" , I have attached the reference pic above.

I have also attached a screenshot to show the installation confirmation for source setup.sh below.

Kindly let me know where I might be erring. Many thanks in advance.