Comments (3)
YuFengUofR
commented on August 18, 2024
right now, the limited-DA version still can't get comparable accuracy as the original one, the accuracy is ~1%, so I am trying to find where the bug is
from efficient-deep-learning-for-point-clouds.
Boyuan-Tian
commented on August 18, 2024
The bug lies in here, the first layer MLP.
Here the BN and ReLU follow matrix-matrix multiplication in tf_util.conv2d, and then executes sample and group. However, by definition, the limited DA should execute sample and group before BN and ReLU to retain the mathematical equivalence.
from efficient-deep-learning-for-point-clouds.
YuFengUofR
commented on August 18, 2024
upload weights and screenshot for limited-DA
from efficient-deep-learning-for-point-clouds.
Related Issues (11)
- imgs
- pointnet2 seg has no training instructions. HOT 1
- refactor the code so that limited-DA doesn't require re-training
- f-pointnet：a big gap between test in my environment and the your screenshot,can you help me find the problem? HOT 12
- the question about the paper in IV-A HOT 4
- Runtime: I don't know why the time consumption is basically the same as f-pointnet(baseline) 0.011-0.015 s HOT 3
- Low training accuracy with pointnet2 HOT 3
- DGCNN cls has no training instructions HOT 1
- DGCNN seg has no training instructions HOT 1
- fpointnet has no training and evaluation instructions for limited DA. HOT 1
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