LIP: Local Importance-based Pooling

12 Aug 2019Ziteng GaoLimin WangGangshan Wu

Spatial downsampling layers are favored in convolutional neural networks (CNNs) to downscale feature maps for larger receptive fields and less memory consumption. However, for discriminative tasks, there are possibilities that these layers lose the discriminative details due to improper pooling strategies, which could hinder the learning process and eventually result in suboptimal models... (read more)

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