TY - GEN
T1 - Generative Adversarial Networks-based Face Hallucination with Identity-Preserving
AU - Yeh, Chia Hung
AU - Chiu, Daniel
AU - Kang, Li Wei
AU - Hsu, Chih Chung
AU - Lo, Chen
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - This paper presents a novel generative adversarial networks-based face hallucination framework for producing high-resolution face images from very low-resolution (LR) ones. We propose a multi-scale generator architecture with multi-scale loss functions for different upscaling factors and a triplet-based identity preserving loss for extracting multi-scale identity-aware facial representations. Experimental results have verified that our method can well super-resolve very LR face images (e.g., 8×8) quantitatively and qualitatively.
AB - This paper presents a novel generative adversarial networks-based face hallucination framework for producing high-resolution face images from very low-resolution (LR) ones. We propose a multi-scale generator architecture with multi-scale loss functions for different upscaling factors and a triplet-based identity preserving loss for extracting multi-scale identity-aware facial representations. Experimental results have verified that our method can well super-resolve very LR face images (e.g., 8×8) quantitatively and qualitatively.
UR - http://www.scopus.com/inward/record.url?scp=85123054202&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85123054202&partnerID=8YFLogxK
U2 - 10.1109/ICCE-TW52618.2021.9603171
DO - 10.1109/ICCE-TW52618.2021.9603171
M3 - Conference contribution
AN - SCOPUS:85123054202
T3 - 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
BT - 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
Y2 - 15 September 2021 through 17 September 2021
ER -