We propose a novel two-phase framework by designating two separate networks to tackle editing and reconstruction respectively, instead of balancing the two.
Feb 7, 2023 · In Phase II, a carefully designed rectifying network is utilized to rectify the inversion errors and perform ideal reconstruction. Experimental ...
The StyleGAN family succeed in high-fidelity image generation and allow for flexible and plausible editing of generated images by manipulating the ...
ReGANIE: Rectifying GAN Inversion Errors for Accurate Real Image Editing. ... Balancing Reconstruction and Editing Quality of GAN Inversion for Real Image Editing ...
ReGANIE: Rectifying GAN Inversion Errors for Accurate Real Image Editing. Proceedings of the AAAI Conference on Artificial Intelligence, 37(1), 1269-1277 ...
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为了从根本上解决这个问题,我们提出了一个新的两阶段框架,指定两个独立的网络分别处理编辑和重建,而不是平衡两者。具体来说,在第一阶段,训练了一个面向W ...
ReGANIE: Rectifying GAN Inversion Errors for Accurate Real Image Editing Bingchuan Li, Tiangxiang Ma, Peng Zhang, Miao Hua, Wei Liu, Qian He, and Zili Yi
In this paper, we introduce a novel Geometry-aware Facial Expression Translation (GaFET) framework, which is based on parametric 3D facial representations.
ReGANIE: Rectifying GAN Inversion Errors for Accurate Real Image Editing · Published: 31 Dec 2022, Last Modified: 12 May 2023 · CoRR 2023 · Readers: Everyone ...