Transcription of Fast Fourier Convolution - NIPS
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Fast Fourier Convolution - NIPS
fast Fourier ConvolutionLu Chi1, Borui Jiang2, Yadong Mu1 1 Wangxuan Institute of Computer Technology,2 Center for Data SciencePeking convolutions in modern deep networks are known to operate locally and atfixed scale ( , the widely-adopted3 3kernels in image-oriented tasks). Thiscauses low efficacy in connecting two distant locations in the network. In this work,we propose a novel convolutional operator dubbed asfast Fourier Convolution (FFC), which has the main hallmarks of non-local receptive fields and cross-scalefusion within the convolutional unit. According to spectral Convolution theorem inFourier theory, point-wise update in the spectral domain globally affects all inputfeatures involved in Fourier transform, which sheds light on neural architecturaldesign with non-local receptive field.
Fast Fourier Convolution Lu Chi 1, Borui Jiang2, Yadong Mu 1Wangxuan Institute of Computer Technology, 2Center for Data Science Peking University {chilu,jbr,myd}@pku.edu.cn Abstract Vanilla convolutions in modern deep networks are known to operate locally and at fixed scale (e.g., the widely-adopted 3 3 kernels in image-oriented tasks). This
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