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    TimeSformer

    TimeSformer

    The official pytorch implementation of our paper

    ...TimeSformer was influential in showing that pure transformer architectures—without convolutional backbones—can perform strongly on video classification tasks. Its flexible attention design allows experimenting with different factoring (spatial-then-temporal, joint, etc.) to trade off compute, memory, and accuracy.
    Downloads: 1 This Week
    Last Update:
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  • 2
    This is an image coder with fixed sampling, at a rate of up to 24 images per second (on XC2V1000-4 @ 40 MHz with res. up to 352x288).
    Downloads: 1 This Week
    Last Update:
    See Project
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