Faithful extreme rescaling via generative prior reciprocated invertible representations

• Main Authors: ZHONG, Zhixuan, CHAI, Liangyu, ZHOU, Yang, DENG, Bailin, PAN, Jia, HE, Shengfeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Face and gestures; Image and video synthesis and generation; Low-level vision; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8444; https://ink.library.smu.edu.sg/context/sis_research/article/9447/viewcontent/Zhong_Faithful_Extreme_Rescaling_via_Generative_Prior_Reciprocated_Invertible_Representations_CVPR_2022_paper.pdf
• Institution: Singapore Management University

This paper presents a Generative prior ReciprocAted Invertible rescaling Network (GRAIN) for generating faithful high-resolution (HR) images from low-resolution (LR) invertible images with an extreme upscaling factor (64×). Previous researches have leveraged the prior knowledge of a pretrained GAN m...