Convolutional Mean: A Simple Convolutional Neural Network for Illuminant Estimation

Han Gong (University of East Anglia)

Abstract
We present Convolutional Mean (CM) – a simple and fast convolutional neural network for illuminant estimation. Our proposed method only requires a small neural network model (1.1K parameters) and a 48 × 32 thumbnail input image. Our unoptimized Python implementation takes 1 ms/image, which is arguably 3-3750× faster than the current leading solutions with similar accuracy. Using two public datasets, we show that our proposed light-weight method offers accuracy comparable to the current leading methods’ (which consist of thousands/millions of parameters) across several measures.

DOI
10.5244/C.33.36
https://dx.doi.org/10.5244/C.33.36

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