Open davidGCR opened 3 years ago
It's true that the original C3D networks have 3 FC layers (VGG-style, has much more parameters and is easier to be overfitted on small datasets). Here, we keep the feature extractor (ConvNet part), and replace FC layers with GAP and one FC layer, like most of modern networks do.
As for loading the pretrained model, specifically in PyTorch, just set strict=False
in load_state_dict()
. Please see here.
Thank you for your answer. I am getting the batch losses with NaN during C3D training using your code. Some idea why?.
Hi, great work. In your code, have you defined the original C3D model?. The pretrained model have three fully conected layers, and your implementation have only one. How are you loading this pretrained model?.