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Facial Action Unit Recognition Enhanced by Text Descriptions of FACS

IEEE Transactions on Affective computing 2024年第02期16卷 814-826页

作者： Chang, Yanan Zhang, Caichao Wu, Yi Wang, Shangfei University of Science and Technology of China Key Lab of Computing and Communication Software of Anhui Province Anhui Hefei230027 China

Although the descriptions of facial action units (AUs) provide crucial semantic knowledge for representation learning from facial images, they have not been fully explored for facial action unit recognition. In this paper, we propose a method that effectively explores the knowledge existing in AU descriptions to enhance AU recognition. Specifically, the proposed method consists of three components, i.e. AU recognition network, global representation alignment, and AU representation alignment. The AU recognition network extracts global features and AU-specific features for AU prediction from images. To leverage AU textual descriptions fully, we design two-level representation alignment for AU recognition. The global representation alignment component closes the distance between the global facial features and its corresponding positive global embedding extracted from textual descriptions. Then, the AU-specific features are aligned with the positive AU textual embedding by the AU representation alignment component. Negative textual embedding generation strategies are also designed to further boost the two-level representation alignment. Through the two-level alignment, AU textual descriptions guide image representation learning of the AU recognition network. Experiments on two benchmark datasets and one in-the-wild dataset demonstrate the efficacy of the description-enhanced AU recognition method, compared with the state-of-the-art works. © 2010-2012 IEEE.

关键词： Contrastive Learning

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PR3D: Precise and realistic 3D face reconstruction from a single image

PR3D: Precise and realistic 3D face reconstruction from a si...

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作者： Huang, Zhangjin Wu, Xing University of Science and Technology of China Hefei China Anhui Province Key Laboratory of Software in Computing and Communication Hefei China Deqing Alpha Innovation Institute Huzhou China

Reconstructing the three-dimensional (3D) shape and texture of the face from a single image is a significant and challenging task in computer vision and graphics. In recent years, learning-based reconstruction methods have exhibited outstanding performance, but their effectiveness is severely constrained by the scarcity of available training data with 3D annotations. To address this issue, we present the PR3D (Precise and Realistic 3D face reconstruction) method, which consists of high-precision shape reconstruction based on semi-supervised learning and high-fidelity texture reconstruction based on StyleGAN2. In shape reconstruction, we use in-the-wild face images and 3D annotated datasets to train the auxiliary encoder and the identity encoder, encoding the input image into parameters of FLAME (a parametric 3D face model). Simultaneously, a novel semi-supervised hybrid landmark loss is designed to more effectively learn from in-the-wild face images and 3D annotated datasets. Furthermore, to meet the real-time requirements in practical applications, a lightweight shape reconstruction model called fast-PR3D is distilled through teacher–student learning. In texture reconstruction, we propose a texture extraction method based on face reenactment in StyleGAN2 style space, extracting texture from the source and reenacted face images to constitute a facial texture map. Extensive experiments have demonstrated the state-of-the-art performance of our method. © 2024 John Wiley & Sons Ltd.

关键词： Textures

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Multi-layer network embedding on scc-based network with motif

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Digital communications and Networks 2024年第3期10卷 546-556页

作者： Lu Sun Xiaona Li Mingyue Zhang Liangtian Wan Yun Lin Xianpeng Wang Gang Xu Department of Communication Engineering Institute of Information Science TechnologyDalian Maritime UniversityDalian116026China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province DUT School of Software Technology&DUT-RU International School of Information Science and EngineeringDalian University of TechnologyDalian 116620China College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China School of Information and Communication Engineering Hainan UniversityHaikou 570228China State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China

Interconnection of all things challenges the traditional communication methods,and Semantic communication and computing(SCC)will become new *** is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based *** previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node ***,the content of semantic information is quite *** graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of ***,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology *** Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node *** verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

关键词： Semantic communication and computing Multi-layer network Graph neural network Motif

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Low-Resolution Face Recognition Enhanced by High-Resolution Facial Images 17

Low-Resolution Face Recognition Enhanced by High-Resolution ...

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17th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2023

作者： Wang, Haihan Wang, Shangfei University of Science and Technology of China Key Lab of Computing and Communication Software of Anhui Province China University of Science and Technology of China Anhui Robot Technology Standard Innovation Base China

ISBN: (纸本)9798350345445

Despite recent advances in high-resolution (HR) face recognition, recognizing identities from low-resolution (LR) facial images remains challenging due to the absence of facial shape and detail. Current research focuses solely on reducing the distribution discrepancy between the HR and LR embeddings from the output layer, rather than thoroughly investigating the superiority of HR facial images for improved performance. In this paper, we propose a novel low-resolution face recognition method enhanced by the guidance of high-resolution facial images in both feature map space and embedding space. Specifically, in feature map space, the similarity constraint across the multilayer feature maps is adopted to align the intermediate features of facial images. Then we introduce multiple generators to recover HR images from extracted feature maps and utilize the reconstructed loss to supplement the missing facial details in LR images. In embedding space, we propose a supervised auxiliary contrastive loss to encourage the paired HR and LR embedding from the same class to be pulled together, whereas those from different classes are pushed apart. The one-to-many matching strategy and the adaptive weight adjustment strategy are applied to make the network adapt to the inputs of different resolutions. Experiments on four benchmark datasets with both synthesized and realistic LR facial images demonstrate the superiority of the proposed method to state-of-the-art. © 2023 IEEE.

关键词： Embeddings

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Human Pose Estimation with Shape Aware Loss 17

Human Pose Estimation with Shape Aware Loss

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17th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2023

作者： Fang, Lin Wang, Shangfei University of Science and Technology of China Key Lab of Computing and Communication Software of Anhui Province China University of Science and Technology of China Anhui Robot Technology Standard Innovation Base China

ISBN: (纸本)9798350345445

Although the mean square error (mse) of heatmap is an intuitive loss for heatmap-based human pose estimation, the joints localization accuracy may not be improved when heatmap mse reduces. In this paper, we show that a great cause for such misalignment is the unnecessary requirement from heatmap mse on the irrelevant Gaussian parameter, i.e. maximum. The coordinate prediction is precise as long as the probability distribution held by the predicted heatmap is a well-shaped Gaussian distribution and has the same center as the ground truth. However, heatmap mse unnecessarily requires the Gaussian distribution to hold the same maximum as the ground truth. Correspondingly, we introduce mse on the image gradients of the target and predicted heatmap (referred to as gradmap mse) to focus on the shape of the heatmap. Combining heatmap and gradmap mse, we propose a simple yet effective Shape Aware Loss (SAL) method. Being model-agnostic, our method can benefit various existing models. We apply SAL to the three latest network architectures and obtain performance improvements for all of them. Comparisons of the visualized predicted heatmaps further prove the effectiveness of the proposed method. © 2023 IEEE.

关键词： Mean square error

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Constraint-aware and multi-objective optimization for micro-service composition in mobile edge computing

Constraint-aware and multi-objective optimization for micro-...

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作者： Wu, Jintao Zhang, Jingyi Zhang, Yiwen Wen, Yiping School of Software Nanjing University of Information Science and Technology Nanjing China School of Computer Science and Technology Anhui University Anhui China Hunan Key Laboratory for Service Computing and Novel Software Technology Hunan University of Science and Technology Hunan China

As a new paradigm of distributed computing, mobile edge computing (MEC) has gained increasing attention due to its ability to expand the capabilities of centralized cloud computing. In MEC environments, a software application typically consists of multiple micro-services, which can be composed together in a flexible manner to achieve various user requests. However, the composition of micro-services in MEC is still a challenging research issue arising from three aspects. Firstly, composite micro-services constructed by ignoring the processing capabilities of different micro-services may cause waste of edge resources. Secondly, edge servers' limitations in terms of computational power can easily cause service occupancy between composite micro-services, severely affecting the user experience. Thirdly, in dynamic and unstable mobile environments, different edge users have different sensitivities to request latency, which increases the complexity of micro-service composition. In order to improve edge resource utilization and user experience on micro-service invocations, in this paper, we comprehensively consider the above three factors, and we first model the micro-services composition problem in MEC as a constrained multi-objective optimization problem. Then, a micro-service composition optimization method M3C combining graph search and branch-and-bound strategy is proposed to find a composition solution set with low energy consumption and high success rate for multiple edge users. Finally, we perform a series of experiments on two widely used datasets. Experimental results show that our proposed approach significantly outperforms the four competing baseline approaches, and that it is sufficiently efficient for practical deployment. © 2023 John Wiley & Sons Ltd.

关键词： Multiobjective optimization

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Linguistic Steganalysis Based on Meta Features and Immune Mechanism

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Chinese Journal of Electronics 2023年第4期19卷 661-666页

作者： Hao Yang Xianbin Cao Anhui Province Key Laboratory of Software in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei China

Linguistic steganalysis depends on efficient detection features due to the diversity of syntax and the polysemia of semantics in natural language processing. This paper presents a novel linguistics steganalysis approach based on meta features and immune clone mechanism. Firstly, meta features are used to represent texts. Then immune clone mechanism is exploited to select appropriate features so as to constitute effective detectors. Our approach employed meta features as detection features, which is an opposite view from the previous literatures. Moreover, the immune training process consists of two phases which can identify respectively two kinds of stego texts. The constituted detectors have the capable of blind steganalysis to a certain extent. Experiments show that the proposed approach gets better performance than typical existing methods, especially in detecting short texts. When sizes of texts are confined to 3kB, detection accuracies have exceeded 95%.

关键词： Training Integrated circuits Steganography Semantics Cloning Detectors Linguistics

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Adaptive Step-Size Sparse Millimeter Wave Imaging Algorithm Based on Approximate Observations 11

Adaptive Step-Size Sparse Millimeter Wave Imaging Algorithm ...

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11th IEEE International Conference on Computer Science and Network Technology, ICCSNT 2023

作者： Wang, Dianhao Huang, Xinqi Yu, Canping Mao, Qi Li, Yingsong College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

ISBN: (纸本)9798350311594

The currently constructed millimeter wave imaging system has the problems of long sampling time and more sampling points of antenna units, and the use of compressed perception algorithm can improve the imaging quality when the number of sampling points are much smaller than the Nyquist distance sampling. The traditional compressed perception algorithm can achieve better sparse recovery than the matched filter imaging algorithm, but there is a large dimension of the measurement matrix and high computational complexity. For the problems of difficult data processing and large dimensions of measurement matrix, a sparse imaging regularization model is constructed based on approximate observation, and an improved soft threshold iterative algorithm is used with adaptive step size, which improves the convergence performance, reduces the computational complexity of the sparse recovery dramatically and achieves a better quality of sparse imaging than the traditional compressed perception algorithm. © 2023 IEEE.

关键词： Computational complexity

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A Dual-band Low-profile Quadrifilar-Helix Antenna for Satellite Navigation System

A Dual-band Low-profile Quadrifilar-Helix Antenna for Satell...

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2023 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2023

作者： Wang, Jiahong Qi, Junwei Li, Yingsong Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

ISBN: (纸本)9798350336740

A new dual-band low-profile quadrifilar-helical antenna (QHA) was presented. The spiral radiation arm of QHA is printed to three circular dielectric plates to reduce the antenna height. In this case, the radiation arm of the lower layer is connected to the feed, and the L-shaped branch is connected to the ground through a 50 ohm resistance. The radiation arm in the middle layer adds branches to realize dual frequency. The upper radiation arm rotates inward and folds, further realizing miniaturization. As a result, the height of QHA is only 20mm. Through CST simulation and optimization, The operating frequency bands of QHA are 1GHz - 1.45GHz and 1.54GHz - 1.74GHz. The beam width of QHA is more than 120°, which is to provide service for satellite navigating systems. The AR for the operation bands are less than 3dB. © 2023 IEEE.

关键词： Satellites

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Affine-Projection Maximum Asymmetric Correntropy Criterion Algorithm Under System Identifications 11

Affine-Projection Maximum Asymmetric Correntropy Criterion A...

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11th IEEE International Conference on Computer Science and Network Technology, ICCSNT 2023

作者： Peng, Yan Huang, Xinqi Yu, Canping Mao, Qi Li, Yingsong College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

ISBN: (纸本)9798350311594

The Affine-Projection Maximum Asymmetric Correntropy Criterion (APMACC) is constructed, drawing upon the fundamental principles of the maximum asymmetric correntropy criterion and an affine-projection scheme. The APMACC algorithm incorporates the asymmetric Gaussian model as a kernel function within the Affine-Projection (AP) algorithm framework, thereby endowing it with robustness against asymmetrically distributed noise. Furthermore, the bound for step-size is established in the literature. Simulation results demonstrate that the APMACC has fast convergence and low steady-state. © 2023 IEEE.

关键词： Adaptive filtering

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