论文标题
SDE-AWB：第二次国际照明估算挑战的通用解决方案
SDE-AWB: a Generic Solution for 2nd International Illumination Estimation Challenge
论文作者
论文摘要
我们提出了一个基于神经网络的解决方案，用于第二个国际照明估计挑战的三个不同轨道（Chormatomity.iitp.ru）。我们的方法建立在预先训练的挤压网络主链，差异2D染色体直方图层和使用EXIF信息的浅MLP上。通过结合语义特征，颜色特征和Exif元数据，由此产生的方法-SDE-AWB-在室内和两弹性轨道中获得第一名，并在一般轨道中获得第二名。
We propose a neural network-based solution for three different tracks of 2nd International Illumination Estimation Challenge (chromaticity.iitp.ru). Our method is built on pre-trained Squeeze-Net backbone, differential 2D chroma histogram layer and a shallow MLP utilizing Exif information. By combining semantic feature, color feature and Exif metadata, the resulting method -- SDE-AWB -- obtains 1st place in both indoor and two-illuminant tracks and 2nd place in general track.
