HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment

11 May 2020Lingbo YangChang LiuPan WangShanshe WangPeiran RenSiwei MaWen Gao

Existing face restoration researches typically relies on either the degradation prior or explicit guidance labels for training, which often results in limited generalization ability over real-world images with heterogeneous degradations and rich background contents. In this paper, we investigate the more challenging and practical "dual-blind" version of the problem by lifting the requirements on both types of prior, termed as "Face Renovation"(FR)... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Face Hallucination FFHQ 512 x 512 - 16x upscaling HiFaceGAN FID 11.389 # 1
LPIPS 0.2449 # 1
NIQE 6.767 # 1

Methods used in the Paper


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