completion3d
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Source code for baselines of the Stanford 3D Point Cloud Completion Benchmark (completion3d.stanford.edu) and TopNet: Structural Point Cloud Decoder, CVPR 2019
Is this dataset still available for downloading? The link in the [project webpage](https://completion3d.stanford.edu/) has no response...
Bumps [numpy](https://github.com/numpy/numpy) from 1.16.3 to 1.22.0. Release notes Sourced from numpy's releases. v1.22.0 NumPy 1.22.0 Release Notes NumPy 1.22.0 is a big release featuring the work of 153 contributors spread...
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Hi~ I have trouble submitting my results. I'm sure that the format of my submission is matched with yours but I still can't submit results and get 'Please be patient...
Bumps [tensorflow-gpu](https://github.com/tensorflow/tensorflow) from 1.12.0 to 2.7.2. Release notes Sourced from tensorflow-gpu's releases. TensorFlow 2.7.2 Release 2.7.2 This releases introduces several vulnerability fixes: Fixes a code injection in saved_model_cli (CVE-2022-29216) Fixes...
Hello, thanks a lot for your great work! Currently, I am trying to integrate the "completion3d" dataset into [torch-point3d](https://github.com/tuda-fub/torch-points3d/tree/pcn_impl). To load the point cloud "h5" files I just used the...
Hi, what's your test data "*.h5" order? Are you following the test.list? Why did you rename them from "0000.h5" to "1199.h5"?
the code for the tree structure is just residual connection? The novel decoder is just mutiple use of folding net?
I followed the instruction to train the topnet for 300 epochs using the data provided. However, the results don't seem as good as the paper presents. Could you please provide...
In the TopNet paper, there is a version to generate N=16384 points. For N=2048, it is clearly demonstrated in the Sec. 4.2: > When generating N = 2048 points, the...
Hi, When I follow the instructions to train a TopNet model with 16384 output points, I found the batchsize can be only set to 1 for the high memory occupation...
