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17th Asian Conference on Computer Vision, ACCV 2024

作者： Ma, Jing Xiang, Xiang He, Yan National Key Lab of Multi-Spectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9789819609161

Few-shot Font Generation (FFG) is a practical technology widely used in designing artistic characters, handwriting imitation, and identification, etc., which aims to generate realistic font images with a few reference samples. Typically, convolutional neural networks (CNNs) are employed to learn the representations of style and content from the font images. However, owing to the locality of convolutional operations, CNNs are not good at capturing the global structure of fonts, which leads to the generated images with blurry components and distorted space layouts. To address this problem, we consider cascading self-attention modules to exploit long-range dependencies for font generation and propose a transformer-based approach called FGTr. Following the style-content disentanglement paradigm, FGTr contains two different transformer encoders to extract the style and content sequences. A multi-layer transformer decoder is adopted to merge the two sequences and generate target images. In order to smoothen the transition of patch edges, we utilize a Local Self-Attention Mask (LSAM) to restrict the attention scope of each patch to a fixed-size sliding window, which plugs into the Transformer with no extra parameters. We also propose an Auxiliary Generation Module (AGM) in favor of generating glyphs closer to the real. Extensive experiments demonstrate the effectiveness and superiority of our method compared with state-of-the-art CNN-based models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolution

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Learning Visual-Semantic Hierarchical Attribute Space for Interpretable Open-Set Recognition

Learning Visual-Semantic Hierarchical Attribute Space for In...

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2025 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2025

作者： Xu, Zhuo Xiang, Xiang School of Artificial Intelligence and Automation Huazhong University of Science and Technology National Key Lab of Multi-Spectral Information Intelligent Processing Technology Wuhan China Peng Cheng Lab China

ISBN: (纸本)9798331510831

In the field of open-set recognition, conventional models often focus on addressing challenges within a single hierarchical category, and these methods frequently lack inter-pretability. In this paper, we propose a novel solution that utilizes attributes and hierarchical relationships to achieve interpretable open-set recognition. Our method is centered around the visual-semantic attribute space. By leveraging hierarchy division, we can decompose the attributes into more granular components, thereby yielding additional performance improvements. When confronted with an unfamiliar object, our method not only classifies it as an unknown category but also provides insights into the broader category and its associated attributes. This capability enhances interpretability by offering valuable information regarding the potential category and characteristics of the object. Experimental results demonstrate great performance improvements compared to existing methods. © 2025 IEEE.

关键词： Hierarchical systems

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Learning Visual-Semantic Hierarchical Attribute Space for Interpretable Open-Set Recognition

Learning Visual-Semantic Hierarchical Attribute Space for In...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Zhuo Xu Xiang Xiang National Key Lab of Multi-Spectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

关键词： Computer vision Computational modeling

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Rate-Splitting multiple Access Enabled Green Probabilistic Semantic Communication over Wireless Networks

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2025年

作者： Xu, Ruopeng Yang, Zhaohui Mao, Yijie Huang, Chongwen Yang, Qianqian Xu, Lexi Xu, Wei Zhang, Zhaoyang Zhejiang University College of Information Science and Electronic Engineering China Hangzhou310027 China ShanghaiTech University School of Information Science and Technology Shanghai201210 China Zhejiang Prov. Key Lab. of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China China United Network Communications Corporation Research Institute Beijing100048 China Southeast University National Mobile Communications Research Laboratory Nanjing211189 China

In this paper, we propose a multi-user green probabilistic semantic communication (PSC) system for semantic communication (SemCom) facilitated by probabilistic knowledge graphs (PKGs), which are knowledge graphs (KGs) integrated with probability to represent semantic information. In the considered model, semantic information of different users is represented by PKGs. On this basis, we design a semantic compression model for multi-user downlink task-oriented SemCom, utilizing the semantic compression ratio (SCR) as a parameter to connect the computation and communication processes of information transmission. Utilizing rate-splitting multiple access (RSMA) technology, the transmitted messages are splitted into shared and private ones. Considering the limited wireless resources and constraint in semantic communication, an optimization problem with the goal of minimizing system energy consumption comprehensively considering the computation and communication process is formulated. In order to address the optimization problem, we propose an alternating optimization algorithm that tackles sub-problems of power allocation and beamforming design with successive convex approximation (SCA) method, semantic compression ratio optimization with variable substitution method, and computation capacity allocation with obtaining closed-form optimal solution. Simulation results verify the effectiveness of the proposed algorithm. © 2017 IEEE.

关键词： Knowledge graph

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Pulsar/CNS integrated navigation based on federated UKF

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Journal of Systems Engineering and Electronics 2010年第4期21卷 675-681页

作者： Jin Liu Jie Ma Jinwen Tian State Key Laboratory for Multi-spectral Information Processing Technologies Institue for Pattern Recognition and artifical Intelligence Huazhong University of Science and Technology Wuhan 430074 P. R. China

In order to improve the autonomous navigation capability of satellite,a pulsar/CNS（celestial navigation system） integrated navigation method based on federated unscented Kalman filter（UKF） is *** celestial navigation is a mature and stable navigation ***,its position determination performance is not satisfied due to the low accuracy of horizon *** pulsar navigation is a new navigation method,which can provide highly accurate range *** major drawback of single pulsar navigation is that the system is completely *** two methods are complementary to each other,the federated UKF is used here for fusing the navigation data from single pulsar navigation and *** to the traditional celestial navigation method and single pulsar navigation,the integrated navigation method can provide better navigation *** simulation results demonstrate the feasibility and effectiveness of the navigation method.

关键词： autonomous navigation celestial navigation system(CNS) pulsar federated unscented Kalman filter(UKF).

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The NeRF Signature: Codebook-Aided Watermarking for Neural Radiance Fields

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第6期47卷 4652-4667页

作者： Ziyuan Luo Anderson Rocha Boxin Shi Qing Guo Haoliang Li Renjie Wan Department of Computer Science Hong Kong Baptist University Hong Kong SAR China Artificial Intelligence Lab. Recod.ai Institute of Computing University of Campinas Campinas Brazil State Key Laboratory of Multimedia Information Processing and National Engineering Research Center of Visual Technology School of Computer Science Peking University Beijing China IHPC and CFAR Agency for Science Technology and Research (A*STAR) Singapore Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong

Neural Radiance Fields (NeRF) have been gaining attention as a significant form of 3D content representation. With the proliferation of NeRF-based creations, the need for copyright protection has emerged as a critical issue. Although some approaches have been proposed to embed digital watermarks into NeRF, they often neglect essential model-level considerations and incur substantial time overheads, resulting in reduced imperceptibility and robustness, along with user inconvenience. In this paper, we extend the previous criteria for image watermarking to the model level and propose NeRF Signature, a novel watermarking method for NeRF. We employ a Codebook-aided Signature Embedding (CSE) that does not alter the model structure, thereby maintaining imperceptibility and enhancing robustness at the model level. Furthermore, after optimization, any desired signatures can be embedded through the CSE, and no fine-tuning is required when NeRF owners want to use new binary signatures. Then, we introduce a joint pose-patch encryption watermarking strategy to hide signatures into patches rendered from a specific viewpoint for higher robustness. In addition, we explore a Complexity-Aware key Selection (CAKS) scheme to embed signatures in high visual complexity patches to enhance imperceptibility. The experimental results demonstrate that our method outperforms other baseline methods in terms of imperceptibility and robustness.

关键词： Neural radiance field Watermarking Three-dimensional displays Training Robustness Pipelines Computational modeling Visualization Solid modeling Rendering (computer graphics)

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Efficient systolic implementation of DFT using only the first-order moments

Efficient systolic implementation of DFT using only the firs...

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2010 International Conference on Intelligent Control and information processing, ICICIP 2010

作者： Liu, Jianguo Liu, Zhenbing Pan, Chao State Key Lab. for Multi-Spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424470488

The Discrete Fourier transform (DFT) is an important tool in digital signal processing. In this paper, a novel approach to DFT is proposed. The computation of DFT is transformed to the computation of the first-order moments by the simple mathematical deductions. It is well known that the first-order moments can be computed efficiently using only additions. An efficient systolic array is designed to implement DFT. The comparison with the existing methods shows the advantages of our method. The approach is also applicable to DFT inverses. © 2010 IEEE.

关键词： Discrete Fourier transforms

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Intensity-based correlation for heterogeneous images scene matching

Intensity-based correlation for heterogeneous images scene m...

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MIPPR 2007: Automatic Target Recognition and Image Analysis;and multispectral Image Acquisition

作者： Sheng, Zhong Huimin, Cao Tianxu, Zhang State Key Lab. for Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819469502

Downward looking scene matching is an important technique of the aircraft automation guidance. To solve the heterogeneous images scene matching problem, we present two effective methods based on intensity-based correlation in this paper. One is to search the real match position based on the feature of the peak on the correlation surface. We propose a criterion to search the proper matching. The other is to use a non-linear filter to pre-process the images, which reduces the influence of ambient lighting while keeping the necessary image details since the contour of the scene is the stable and unchanged feature. Also, we use a Fourier analysis to explain the contribution of different frequency spectrum in the correlation. By using this frequency information, we propose a simpler kernel filter method based on pre-process, which has the similar performance with non-linear filter pre-process but has less computation complexity. This simple kernel is more suitable for the embedded DSP real-time application.

关键词： Pattern matching

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Design and implementation of a scalab.e enhanced high-performance DMA architecture for complex SoC

Design and implementation of a scalable enhanced high-perfor...

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MIPPR 2009 - Medical Imaging, Parallel processing of Images, and Optimization Techniques: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Zhao, Hualong Sang, Hongshi Zhang, Tianxu Shen, Xubang State Key Lab. for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

As the demand of higher image quality and greater processing capabilities are growing, obtaining higher data bandwidth for on-chip processing is becoming a more and more important issue. DMA (Direct Memory Access) component, as the key element in stream processing SoC (System on Chip) [1], should be deeply researched and designed to satisfy the high data bandwidth requirement of processing units. In this paper, we introduce a scalab.e high-performance DMA architecture for complex SoC to satisfy rigorous high sustained bandwidth and versatile functionality requirements. Several techniques and structures are proposed in this paper. An integrated verification environment is also built for our design to fully verify its functionality. And the performance improvement by using our architecture is analyzed. At the end of the paper, the post-simulation and tape-out results are provided. The whole implementation has been silicon proven to be functional and efficient. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： System-on-chip

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Computational simulation of second order motion perception

Computational simulation of second order motion perception

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MIPPR 2007: Automatic Target Recognition and Image Analysis;and multispectral Image Acquisition

作者： Bin, Sun Nong, Sang State Key Lab. for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819469502

Physiological studies have provided clear evidence of neurons sensitive to second-order motion, and first-order motion mechanisms are blind to second-order motion. In this paper, we propose a computational simulation of second order motion perception, which bases on energy-based detector with a preceded nonlinear process called texture grabber. Generally, a texture grabber consists of a linear spatial filter, a linear temporal filter and a nonlinear transform, such as full-wave rectification. Here Difference of Gaussians (DoG) functions are used as the spatial filters, and Difference of Gammas (DoGamma) functions are chosen as the temporal filters. A series of experiments are computed and the results confirm that our motion perception system detects second-order motion correctly.

关键词： Motion estimation

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