dwofk / fast-depth

ICRA 2019 "FastDepth: Fast Monocular Depth Estimation on Embedded Systems"
MIT License
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Weights [M] in the paper (FastDepth) is inconsistency with this codes #33

Open OscarMind opened 4 years ago

OscarMind commented 4 years ago

The Weights [M] of MobileNet-NNConv5 with depthwise & skip-add in the paper FastDepth: Fast Monocular Depth Estimation on Embedded Systems is 3.93. But I statistic the parameters is 3.96093 by the class MobileNetSkipAdd(nn.Module): in your code.

I want to konw is it a mistake in your paper?

when I reset the kernel size of NNConv5 by 3 instead 5, and the parameters is 3.929186 ≈ 3.93

the following code is used: print('# generator parameters:', 1.0 * sum(param.numel() for param in model.parameters())/1000000)