Comments (4)
φ stands for multiple MLP with Relu, sometimes with a Maxpool at the end.
from efficient-deep-learning-for-point-clouds.
Thanks for your reply:)
maybe my example is not appropriate,when φ stands for multiple MLP with Relu, I still can't deducing it.
could you give me some inspire.
from efficient-deep-learning-for-point-clouds.
it is approximation not 100% equal
from efficient-deep-learning-for-point-clouds.
thanks~
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
- 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
- fpointnet has no screenshot for limited DA. the screenshot contains too many meaningless details. HOT 3
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