Comments (1)
In testing, we do not use multi-scale input. This ensures a fair comparison with other methods. The option is just there for future use. Scale jittering is only used in training.
The problem of your inception models come from the different convention used in inferring the output sizes. When the kernel size cannot divide the input size, the pooling layers and convolution layers of Caffe will get different output sizes from the same input size. So you can choose input sizes that bypass this convention of just change how the layers compute its output sizes.
from temporal-segment-networks.
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from temporal-segment-networks.