Comments (2)
I have this issue too. And also, the segmentation model in your code is quite different from the paper. It seems that you only use edgeconv operation in the first mlp layer in each EdgeConv block for segmentation. While in the classification model, each mlp layer in EdgeConv block do the edgeconv operation.
And the concatenation operation is different from the paper.
@WangYueFt
Sorry to interrupt you, I just make sure that I did not understand it wrong.
from dgcnn.
Hi,
Yes. The concatenation is different from what is in the paper. We will release the code exactly the same with the paper. Stay tuned!
Best,
Yue
from dgcnn.
Related Issues (20)
- There was no model.2048.t7 file in pretrained folder.
- Can I get the final paper?
- pytorch part segmentation HOT 1
- Can we run this code in windows?
- Visualization issues
- getting 'Indexerror' in train_multi_gpu.py HOT 1
- Understanding equation #8 in research paper (Section 3.1)
- 请问你的分类模型到底是哪样的,有的有连接,有的没有!!!
- LiDAR Point Cloud Classification results not good with real data HOT 1
- Why does the pytorch version not have transform? HOT 2
- How to add more DGCNN layers in your implementation?
- Aborted (core dumped) if I process to many points at once HOT 2
- Is the input size of the first layer 6 because the input parameters are the point itself and its normals?? HOT 1
- Why is the accuracy rate so low? HOT 1
- Visualization
- ValueError: need at least one array to concatenate HOT 2
- What is the KNN distance formula implemented by pytorch HOT 1
- The network architecture in code is different from the paper?
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