• Corpus ID: 231846995

Sill-Net: Feature Augmentation with Separated Illumination Representation

  title={Sill-Net: Feature Augmentation with Separated Illumination Representation},
  author={Hanwang Zhang and Zhong Cao and Ziang Yan and Changshui Zhang},
For visual object recognition tasks, the illumination variations can cause distinct changes in object appearance and thus confuse the deep neural network based recognition models. Especially for some rare illumination conditions, collecting sufficient training samples could be time-consuming and expensive. To solve this problem, in this paper we propose a novel neural network architecture called Separating-Illumination Network (Sill-Net). Sill-Net learns to separate illumination features from… 
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