An encoder–decoder based thermo-visible image translation for disguised and undisguised faces
作者：
Highlights：
• An architecture for image translation of disguised and undisguised faces.
• A weighted combination of the loss function for faster convergence.
• Skip connections from the encoder to the decoder for feature utilization.
• Use of deconvolution layer in decoder part.
• Shows better performance compared to GANs.
摘要
Highlights•An architecture for image translation of disguised and undisguised faces.•A weighted combination of the loss function for faster convergence.•Skip connections from the encoder to the decoder for feature utilization.•Use of deconvolution layer in decoder part.•Shows better performance compared to GANs.
论文关键词：Image translation,Generative Adversarial Networks (GAN),Pix2Pix,Cycle-GAN,Encoder–decoder
论文评审过程：Received 20 November 2021, Revised 4 January 2022, Accepted 10 January 2022, Available online 19 January 2022, Version of Record 3 February 2022.
论文官网地址：https://doi.org/10.1016/j.imavis.2022.104376
