Improved generative adversarial network and its application in image oil painting style transfer

作者：

Highlights：

• WGAN-GP has stable gradient and alternating iterative convergence ability.

• WGAN-GP provide good edge and texture details for the migration process

• WGAN-GP provide better performance of image oil painting style migration & reconstruction.

摘要

•WGAN-GP has stable gradient and alternating iterative convergence ability.•WGAN-GP provide good edge and texture details for the migration process•WGAN-GP provide better performance of image oil painting style migration & reconstruction.

论文关键词：Generative adversarial network,Wasserstein distance,Gradient penalty,Total variance loss,Migration and reconstruction of oil painting style

论文评审过程：Received 17 June 2020, Revised 16 November 2020, Accepted 3 December 2020, Available online 7 December 2020, Version of Record 16 December 2020.

论文官网地址：https://doi.org/10.1016/j.imavis.2020.104087