Is it possible to use EfficientNet backbone in TSN?

[alejopaullier96]

Is it possible to use an EfficientNet backbone in TSN? I mean something like this:

model = dict(
    type='Recognizer2D',
    backbone=dict(
        type='EfficientNetB4',
        pretrained='torchvision://efficientnet_b4', <------------- somehow change this
        depth=50,
        norm_eval=False),
    cls_head=dict(
        type='TSNHead',
        num_classes=3,
        in_channels=2048,
        spatial_type='avg',
        consensus=dict(type='AvgConsensus', dim=1),
        dropout_ratio=0.4,
        init_std=0.01),
    train_cfg=None,
    test_cfg=dict(average_clips=None))

I dont know if this is possible. For sure there are no weights in the model zoo for this but maybe if this can be done it can be initialized with PyTorch EfficientNet's weights.

[hukkai]

@alejopaullier96 mmaction is no longer maintained. Please check mmaction2