Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations

Gabriëlle Ras, Luca Ambrogioni, Pim Haselager +2

In this paper we introduce the temporally factorized 3D convolution (3TConv) as an interpretable alternative to the regular 3D convolution (3DConv). In a 3TConv the 3D convolutiona…