Spec-Net and Spec-CGAN: Deep learning models for specularity removal from faces
作者:
Highlights:
• We introduce Spec-Face, the first public specularity data set for human faces.
• We introduce Spec-Net and Spec-CGAN, new deep models for face specularity removal.
• Spec-CGAN performs superior specularity removal for sample images from LFW dataset.
• Spec-Net performs superior specularity removal for Spec-Face and images from LIME.
• Classical methods perform poorly on low chromaticity faces.
摘要
•We introduce Spec-Face, the first public specularity data set for human faces.•We introduce Spec-Net and Spec-CGAN, new deep models for face specularity removal.•Spec-CGAN performs superior specularity removal for sample images from LFW dataset.•Spec-Net performs superior specularity removal for Spec-Face and images from LIME.•Classical methods perform poorly on low chromaticity faces.
论文关键词:Specularity,Dichromatic reflection model,Deep learning,Convolutional neural networks
论文评审过程:Received 1 August 2019, Revised 28 September 2019, Accepted 1 November 2019, Available online 7 November 2019, Version of Record 21 January 2020.
论文官网地址:https://doi.org/10.1016/j.imavis.2019.11.001