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2,069 results on '"Zhou, Man"'

57. Memory-augmented Deep Unfolding Network for Guided Image Super-resolution

Author

Zhou, Man, Yan, Keyu, Pan, Jinshan, Ren, Wenqi, Xie, Qi, and Cao, Xiangyong

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Guided image super-resolution (GISR) aims to obtain a high-resolution (HR) target image by enhancing the spatial resolution of a low-resolution (LR) target image under the guidance of a HR image. However, previous model-based methods mainly takes the entire image as a whole, and assume the prior distribution between the HR target image and the HR guidance image, simply ignoring many non-local common characteristics between them. To alleviate this issue, we firstly propose a maximal a posterior (MAP) estimation model for GISR with two types of prior on the HR target image, i.e., local implicit prior and global implicit prior. The local implicit prior aims to model the complex relationship between the HR target image and the HR guidance image from a local perspective, and the global implicit prior considers the non-local auto-regression property between the two images from a global perspective. Secondly, we design a novel alternating optimization algorithm to solve this model for GISR. The algorithm is in a concise framework that facilitates to be replicated into commonly used deep network structures. Thirdly, to reduce the information loss across iterative stages, the persistent memory mechanism is introduced to augment the information representation by exploiting the Long short-term memory unit (LSTM) in the image and feature spaces. In this way, a deep network with certain interpretation and high representation ability is built. Extensive experimental results validate the superiority of our method on a variety of GISR tasks, including Pan-sharpening, depth image super-resolution, and MR image super-resolution., Comment: 24 pages, 16 figures

Published
2022

63. Unfolding Taylor's Approximations for Image Restoration

Author

Zhou, Man, Xiao, Zeyu, Fu, Xueyang, Liu, Aiping, Yang, Gang, and Xiong, Zhiwei

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Deep learning provides a new avenue for image restoration, which demands a delicate balance between fine-grained details and high-level contextualized information during recovering the latent clear image. In practice, however, existing methods empirically construct encapsulated end-to-end mapping networks without deepening into the rationality, and neglect the intrinsic prior knowledge of restoration task. To solve the above problems, inspired by Taylor's Approximations, we unfold Taylor's Formula to construct a novel framework for image restoration. We find the main part and the derivative part of Taylor's Approximations take the same effect as the two competing goals of high-level contextualized information and spatial details of image restoration respectively. Specifically, our framework consists of two steps, correspondingly responsible for the mapping and derivative functions. The former first learns the high-level contextualized information and the later combines it with the degraded input to progressively recover local high-order spatial details. Our proposed framework is orthogonal to existing methods and thus can be easily integrated with them for further improvement, and extensive experiments demonstrate the effectiveness and scalability of our proposed framework.

Published
2021

82. Securing Face Liveness Detection Using Unforgeable Lip Motion Patterns

Author

Zhou, Man, Wang, Qian, Li, Qi, Jiang, Peipei, Yang, Jingxiao, Shen, Chao, Wang, Cong, and Ding, Shouhong

Subjects
Computer Science - Cryptography and Security
Abstract

Face authentication usually utilizes deep learning models to verify users with high recognition accuracy. However, face authentication systems are vulnerable to various attacks that cheat the models by manipulating the digital counterparts of human faces. So far, lots of liveness detection schemes have been developed to prevent such attacks. Unfortunately, the attacker can still bypass these schemes by constructing wide-ranging sophisticated attacks. We study the security of existing face authentication services (e.g., Microsoft, Amazon, and Face++) and typical liveness detection approaches. Particularly, we develop a new type of attack, i.e., the low-cost 3D projection attack that projects manipulated face videos on a 3D face model, which can easily evade these face authentication services and liveness detection approaches. To this end, we propose FaceLip, a novel liveness detection scheme for face authentication, which utilizes unforgeable lip motion patterns built upon well-designed acoustic signals to enable a strong security guarantee. The unique lip motion patterns for each user are unforgeable because FaceLip verifies the patterns by capturing and analyzing the acoustic signals that are dynamically generated according to random challenges, which ensures that our signals for liveness detection cannot be manipulated. Specially, we develop robust algorithms for FaceLip to eliminate the impact of noisy signals in the environment and thus can accurately infer the lip motions at larger distances. We prototype FaceLip on off-the-shelf smartphones and conduct extensive experiments under different settings. Our evaluation with 44 participants validates the effectiveness and robustness of FaceLip.

Published
2021

83. Preparation and Characterization of Gelatin-Based Antibacterial Film Incorporating Diatomite/Carvacrol Complex

Author

LI Sen, MA Ling, LI Ting, PENG Lu, LI Shasha, LI Qingye, ZHOU Man, WU Hejun

Subjects
diatomite, carvacrol, gelatin, sustained-release, antibacterial film, Food processing and manufacture, TP368-456
Abstract

In this study, diatomite was used as an effective carrier for carvacrol to prepare an antibacterial complex, which was further incorporated into gelatin solution to obtain active composite films. The effect of the addition of the complex on the physical properties and antibacterial activity of gelatin based composite films was investigated. The results of scanning electron microscopy (SEM) and infrared spectroscopy showed that carvacrol was successfully adsorbed to the pores and surface of diatomite. With increasing content of the complex, the thickness, elongation at break, water vapor permeability, oxygen permeability, antioxidant activity and antibacterial activity increased, whereas the light transmission, moisture content, water solubility and tensile strength of the films decreased. Overall, the film with the complex added at 20% showed good performance, whose tensile strength and elongation at break were 15.13 MPa and 67.43%, respectively. The film scavenged 56.33% of 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical, and the inhibition zone diameter of the film against Staphylococcus aureus and Escherichia coli was 39.4 and 23.7 mm, respectively. More importantly, the gelatin film containing diatomite/carvacrol complex exhibited a much slower release rate of carvacrol and longer-acting antibacterial activity than the film containing the same content of carvacrol. These experimental results provide theoretical guidance and an experimental reference for using diatomite to carry carvacrol in developing antibacterial gelatin films with sustained release properties.

Published
2023
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