okankop / Efficient-3DCNNs

PyTorch Implementation of "Resource Efficient 3D Convolutional Neural Networks", codes and pretrained models.
MIT License
773 stars 149 forks source link

Failed to finetune ResNet50 on UCF101 split-1 #33

Open rogercmq opened 3 years ago

rogercmq commented 3 years ago

Hi! There are some implementation details on training 3DCNNs on UCF101 in your paper[1], one of which is "While dropout ratio is kept at 0.2 for Kinetics600 and Jester, it is increased to 0.9 for UCF-101". However, I cannot see any dropout modules in your resnet.py.

So far, I haven't produced the results (88.92% in Tab.8) in your paper. Could you give me an example run of resnet50-ucf101-pretrainK600?

Besides, what is your codebase for I3D?

Regards.

[1] 《Resource Efficient 3D Convolutional Neural Networks》