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Attentive Temporal Pyramid Network for Dynamic Scene Classification

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Figure 1: Framework of the ATP-Net. For a given video sample containing T frames, we extract their CNN features withtThe total number of pyramid CNN subsets areattention matrix ofattention modules in total in whichused for calculating weights of each pyram
Figure 2: The network structure of attention module. 2 batchnormalization layers, 2 Relu activations, 1 attention layerand 1 dropout layer are used in a single attention module.
Table 3: Performance comparison of different algorithms on the YUPENN++, Maryland and Activitynet datasets.

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