Multi-Scale Spatially-Asymmetric Recalibration for Image Classification

Convolution is spatially-symmetric, i.e., the visual features are independent of its position in the image, which limits its ability to utilize contextual cues for visual recognition. This paper addresses this issue by introducing a recalibration process, which refers to the surrounding region of each neuron, computes an importance value and multiplies it to the original neural response... (read more)

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Methods used in the Paper

Activation Functions
Batch Normalization
Residual Block
Skip Connection Blocks
Residual Connection
Skip Connections