Prior-guided dense up-down sampling network for face super-resolution and recognition

Simiao Wang; Yunan Liu; Chunpeng Wang; Mingyu Lu

doi:10.1117/12.2680073

27 June 2023 Prior-guided dense up-down sampling network for face super-resolution and recognition

Simiao Wang, Yunan Liu, Chunpeng Wang, Mingyu Lu

Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 127050F (2023) https://doi.org/10.1117/12.2680073
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China

Abstract

Identifying low-resolution (LR) face images in the wild is still an open and challenging task, 1as discriminative feature is hard to learn from LR image with blurry appearance. To address this problem, many face super-resolution (SR) methods have been proposed to reconstruct high-resolution (HR) face images from the observed LR images. However, most of existing methods have two drawbacks: they tend to generate over-smoothed results, and they largely ignore to recover the facial identity information. In this paper, we propose a new multi-task framework for very small face image SR and recognition. First, we propose the Dense Up-down Sampling Unit (DUSU), which is able to effectively represent the nonlinear LR-to-HR mapping via an error-correcting feedback mechanism. Secondly, we introduce an effective and robust facial prior knowledge, the high frequency sub-bands of Non-Subsampled Contourlet Transform (NSCT), to enhance the texture details of super-resolved images. Third, we introduce an evaluation network with perceptual loss to recover the identity information of reconstructed face images. Extensive experiments demonstrate that our method not only achieves more appealing results than the state-of-the-art methods in terms of traditional SR metrics, but also significantly improve recognition accuracy of very small faces in the wild.

Citation Download Citation

Simiao Wang, Yunan Liu, Chunpeng Wang, and Mingyu Lu "Prior-guided dense up-down sampling network for face super-resolution and recognition", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 127050F (27 June 2023); https://doi.org/10.1117/12.2680073

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Facial recognition systems

Image restoration

Education and training

Lawrencium

Prior knowledge

Face image reconstruction

Visualization

Show All Keywords

Keywords/Phrases

Search In:

Publication Years