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arXiv 2025年

作者： Li, Renkai Yuan, Xin Liu, Wei Xu, Xin School of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System China

Video-based person re-identification (ReID) has become increasingly important due to its applications in video surveillance applications. By employing events in video-based person ReID, more motion information can be provided between continuous frames to improve recognition accuracy. Previous approaches have assisted by introducing event data into the video person ReID task, but they still cannot avoid the privacy leakage problem caused by RGB images. In order to avoid privacy attacks and to take advantage of the benefits of event data, we consider using only event data. To make full use of the information in the event stream, we propose a Cross-Modality and Temporal Collaboration (CMTC) network for event-based video person ReID. First, we design an event transform network to obtain corresponding auxiliary information from the input of raw events. Additionally, we propose a differential modality collaboration module to balance the roles of events and auxiliaries to achieve complementary effects. Furthermore, we introduce a temporal collaboration module to exploit motion information and appearance cues. Experimental results demonstrate that our method outperforms others in the task of event-based video person ReID. Copyright © 2025, The Authors. All rights reserved.

关键词： information leakage

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VAGeo: View-specific Attention for Cross-View Object Geo-Localization

arXiv

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arXiv 2025年

作者： Li, Zhongyang Yuan, Xin Liu, Wei Xu, Xin School of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System China

Cross-view object geo-localization (CVOGL) aims to locate an object of interest in a captured ground- or drone-view image within the satellite image. However, existing works treat ground-view and drone-view query images equivalently, overlooking their inherent viewpoint discrepancies and the spatial correlation between the query image and the satellite-view reference image. To this end, this paper proposes a novel View-specific Attention Geo-localization method (VAGeo) for accurate CVOGL. Specifically, VAGeo contains two key modules: view-specific positional encoding (VSPE) module and channel-spatial hybrid attention (CSHA) module. In object-level, according to the characteristics of different viewpoints of ground and drone query images, viewpoint-specific positional codings are designed to more accurately identify the click-point object of the query image in the VSPE module. In feature-level, a hybrid attention in the CSHA module is introduced by combining channel attention and spatial attention mechanisms simultaneously for learning discriminative features. Extensive experimental results demonstrate that the proposed VAGeo gains a significant performance improvement, i.e., improving acc@0.25/acc@0.5 on the CVOGL dataset from 45.43%/42.24% to 48.21%/45.22% for ground-view, and from 61.97%/57.66% to 66.19%/61.87% for drone-view. Copyright © 2025, The Authors. All rights reserved.

关键词： Encoding (symbols)

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Disentangle Nighttime Lens Flares: Self-supervised Generation-based Lens Flare Removal

arXiv

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arXiv 2025年

作者： He, Yuwen Wang, Wei Wang, Wanyu Jiang, Kui Wu, Wanyu Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology China School of Computer Science and Technology Harbin Institute of Technology China

Lens flares arise from light reflection and refraction within sensor arrays, whose diverse types include glow, veiling glare, reflective flare and so on. Existing methods are specialized for one specific type only, and overlook the simultaneous occurrence of multiple typed lens flares, which is common in the real-world, e.g. coexistence of glow and displacement reflections from the same light source. These co-occurring lens flares cannot be effectively resolved by the simple combination of individual flare removal methods, since these coexisting flares originates from the same light source and are generated simultaneously within the same sensor array, exhibit a complex interdependence rather than simple additive relation. To model this interdependent flares’ relationship, our Nighttime Lens Flare Formation model is the first attempt to learn the intrinsic physical relationship between flares on the imaging plane. Building on this physical model, we introduce a solution to this joint flare removal task named Self-supervised Generation-based Lens Flare Removal Network (SGLFR-Net), which is self-supervised without pre-training. Specifically, the nighttime glow is detangled in PSF Rendering Network(PSFR-Net) based on PSF Rendering Prior, while the reflective flare is modelled in Texture Prior Based Reflection Flare Removal Network (TPRR-Net). Empirical evaluations demonstrate the effectiveness of the proposed method in both joint and individual glare removal tasks. Copyright © 2025, The Authors. All rights reserved.

关键词： Glare

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A novel DEM reconstruction strategy based on multi-frequency In SAR in highly sloped terrain

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Science China(information Sciences) 2017年第8期60卷 243-245页

作者： Tao ZENG Tiandong LIU Zegang DING Qi ZHANG Zhen WANG Teng LONG Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology

Interferometric Synthetic Aperture Radar(InSAR)has been proposed as a technique for the reconstruction of the Digital Elevation Model(DEM),which is widely used in global terrain mapping mission[1].The DEM reconstruction methods of In SAR technique are usually based on the so-called phase unwrapping(PU)*** highly sloped terrain,the interferometric phase gradients(IPG)of the adjacent pixels are more thanπ.Therefore,the traditional PU methods

关键词： SAR In of DEM IPG on Figure LAPS A novel DEM reconstruction strategy based on multi-frequency In SAR in highly sloped terrain

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High-precision deformation monitoring algorithm for GBSAR system: rail determination phase error compensation

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Science China(information Sciences) 2016年第8期59卷 204-219页

作者： Cheng HU Mao ZHU Tao ZENG Weiming TIAN Cong MAO Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology

In recent years, the repeat-pass GBSAR(ground based synthetic aperture radar) system has demonstrated its capacity to acquire deformation. Nevertheless, in a variety of applications, it needs to measure the deformation with the precision up to 0.1 mm, which could not be reached by utilizing the traditional PS(permanent scatterer) algorithm in most cases. Generally, one of the main reasons could be summarized into the phase error caused by the rail determination error, because the precision of rail determination might degrade during long working hours. However, the traditional PS algorithm could not compensate for the phase error caused by the rail determination error. In order to solve the problems, we modify the conventional PS ***, we deduced the transformation relationship between the rail determination error and its corresponding interferometric phase error. Then, the phase errors caused by the atmosphere and the rail determination error were jointly compensated. The experimental data, which were obtained in Fangshan District in Beijing(China), were used to test and verify the performance of the new algorithm. After the comparison between the results processed by the new algorithm and those processed by the traditional algorithm, the proposed method demonstrated its ability to obtain high-precision deformation.

关键词： permanent scatterer(PS) synthetic aperture radar(SAR) ground-based SAR deformation monitoring radar

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Gesture Recognition of sEMG Based on Res-LSTM 17th

Gesture Recognition of sEMG Based on Res-LSTM

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17th International Conference on Intelligent Robotics and Applications, ICIRA 2024

作者： Zhao, Yujia Zou, Chunlong Yun, Juntong Jiang, Du Huang, Li Liu, Ying Jiang, Guozhang Xie, Yuanmin Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

sEMG (surface electromyography) signal control of bionic prostheses has been widely studied over the past few years. In particular, sparse sEMG signals are rapidly developing in the field of gesture recognition for their convenience, noninvasiveness, and ease of access. However, compared with high-density EMG signals, sparse EMG signals lack rich feature information, which in turn affects gesture recognition accuracy. In order to reduce the loss of feature information of sparse EMG signals in the spatio-temporal dimension, this paper proposes a hybrid neural network Res-LSTM combining residual network and long short-term memory network. The ordinary convolutional blocks in the CNN network are replaced with residual blocks, and the final fully connected layer is removed and a constant mapping layer is added to adequate extraction of spatial feature information of the data. The Res layer’s output is utilized as the input for the long and short-term memory (LSTM) network, which further extracts the features of the data in the temporal dimension, and finally completes the categorization output through a fully connected layer. The average accuracy of 91.11% for gesture-motion classification was verified by training on a homebrew dataset;and tested on a public dataset, NinaPro DB1, with an average accuracy of 91.03%. The experimental findings indicate that the proposed Res-LSTM network framework contributes to solving the problem of lack of feature information of sparse sEMG signals and improves the pattern recognition accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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Robust and fast iterative sparse recovery method for space-time adaptive processing

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Science China(information Sciences) 2016年第6期59卷 199-211页

作者： Xiaopeng YANG Yuze SUN Tao ZENG Teng LONG Beijing Key Laboratory of Embedded Real-time Information Processing Technology School of Information and Electronics Beijing Institute of Technology

Conventional space-time adaptive processing(STAP) requires large numbers of independent and identically distributed(i.i.d) training samples to ensure the performance of clutter suppression, which is hard to be achieved in practical complex nonhomogeneous environment. In order to improve the performance of clutter suppression with small training sample support, a robust and fast iterative sparse recovery method for STAP is proposed in this paper. In the proposed method, the sparse recovery of clutter spatial-temporal spectrum and the calibration of space-time overcomplete dictionary are achieved iteratively. Firstly, the robust solution of sparse recovery is derived by regularized processing, which can be calculated recursively based on the block Hermitian matrix property, afterwards the mismatch of space-time overcomplete dictionary is calibrated by minimizing the cost function. The proposed method can not only alleviate the effect of noise and dictionary mismatch, but also reduce the computational cost caused by direct matrix inversion. Finally, the proposed method is verified based on the simulated and the actual airborne phased array radar data, which shows that the proposed method is suitable for practical complex nonhomogeneous environment and provides better performance compared with conventional STAP methods.

关键词： space-time adaptive processing(STAP) sparse recovery robust iteration computational complexity

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A high-precision phase-derived range and velocity measurement method based on synthetic wideband pulse Doppler radar

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Science China(information Sciences) 2017年第8期60卷 151-162页

作者： Huayu FAN Lixiang REN Teng LONG Erke MAO Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Radar Research Laboratory Beijing Institute of Technology

Development of radar technology needs to address the two-dimensional high resolution of range and velocity simultaneously for high-speed targets. Taking advantage of the superior coherent performance of synthetic wideband pulse Doppler radar, this paper elaborates the principles of phase-derived range and velocity measurements. Moreover, this paper explores the key technologies of unwrapping phase ambiguity, and discusses the phase unwrapping strategy at a low signal-to-noise ratio(SNR). The proposed method can be applied to the conditions of low SNR and has comparatively strong practicality in engineering. Both the ejection ball and civil aircraft experiments have validated the correctness and feasibility of the proposed method. In particular,the experimental results reveal that the accuracy of phase-derived range and velocity measurement has reached a level of submillimeter or millimeter and centimeter/second or submillimeter/second, respectively.

关键词： synthetic wideband PD radar phase-derived range measurement phase-derived velocity measurement unwrapping phase ambiguity track filtering minimum entropy method

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A novel subsidence monitoring technique based on space-surface bistatic differential interferometry using GNSS as transmitters

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Science China(information Sciences) 2015年第6期58卷 68-83页

作者： ZENG Tao ZHANG Tian TIAN WeiMing HU Cheng Beijing Key Laboratory of Embedded Real-time Information Processing Technology Radar Research Laboratory School of Information and ElectronicsBeijing Institute of Technology

Synthetic Aperture Radar Differential Interferometry(DIn SAR) technique is an effective tool with large coverage and high spatial accuracy for subsidence monitoring. Nevertheless, the temporal resolution is usually poor so that rapid deformation cannot be measured due to the long revisit time of radar *** SAR Differential Interferometry technique using Global Navigation Satellite System(GNSS) as illuminator has a shorter revisit time, whereas the measurement accuracy is constrained by low signal power, narrow bandwidth and atmospheric delay error. To cope with these problems, in this paper, we propose a novel subsidence monitoring technique based on Space-Surface bistatic Differential Interferometry(SS-DI) with GNSS transmitters, where two stations consist of a reference one and a measurement one that are deployed on the ground. First, we applied a space differential processing between two stations to cancel identical errors such as tropospheric and ionospheric errors etc. Then we used a long time coherent integration to improve the signal noise ratio. Subsequently, we also utilized a time differential processing to construct double differential equations with respect to unknown deformation variables. Finally, we solved the equations to obtain a highly accurate estimation of three dimension deformation. Furthermore, an SS-DI experiment using Beidou-2 as transmitters was carried out to validate the proposed method, where a high accuracy(0.01 mm) device was utilized to simulate subsidence deformation. The experimental results reveal that the proposed method has better performance of spatial measurement accuracy of 0.53 mm compared with differential GPS method.

关键词： differential interferometry subsidence monitoring Beidou-2/Compass-2 space-surface bistatic radar differential GPS

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Impacts of ionospheric scintillation on geosynchronous SAR focusing: preliminary experiments and analysis

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Science China(information Sciences) 2015年第10期58卷 191-193页

作者： LI YuanHao HU Cheng DONG XiChao TIAN WeiMing LONG Teng Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology

Dear editor,Geosynchronous Synthetic Aperture Radar(GEO SAR)has significant potential when applied to hazard and disaster monitoring because of its short revisit time of approximately 24 h and its wide coverage of app... 详细信息

关键词： SAR Impacts of ionospheric scintillation on geosynchronous SAR focusing GEO PSLR Figure preliminary experiments and analysis than

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