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SSRN 2024年

作者： Cao, Jinli Wang, Yanchao Li, Run Zhang, Dawei Li, Minglu Zheng, Zhonglong School of Computer Science and Technology Zhejiang Normal University China State Key Laboratory of CAD&CG Zhejiang University China Key Laboratory of Intelligent Education Technology Application of Zhejiang Province China Department of Computer Science and Information Technology La Trobe University Australia

Multiple Object Tracking (MOT) is a critical task in computer vision with a wide range of practical applications. However, current methods often use a uniform approach for associating all targets, overlooking the varying conditions of each target. This can lead to performance degradation, especially in crowded scenes with dense targets. To address this issue, we propose a novel Condition-Aware Tracking method (CATrack) to differentiate the appearance feature flow for targets under different conditions. Specifically, we propose three designs for data association and feature update. First, we develop an Adaptive Appearance Association Module (AAAM) that selects suitable track templates based on detection conditions, reducing association errors in long-tail cases like occlusions or motion blur. Second, we design an ambiguous track filtering Selective Update strategy (SU) that filters out potential low-quality embeddings. Thus, the noise accumulation in the maintained track feature will also be reduced. Meanwhile, we propose a confidence-based Adaptive EMA (AEMA) method for the feature state transition. By adaptively adjusting the weights of track and detection embeddings, our AEMA better preserves high-quality target features. By integrating the above modules, CATrack enhances the discriminative capability of appearance features and improves the robustness of appearance-based associations. Extensive experiments on the MOT17 and MOT20 benchmarks validate the effectiveness of the proposed CATrack. Notably, the state-of-the-art results on MOT20 demonstrate the superiority of our method in highly crowded scenarios. © 2024, The Authors. All rights reserved.

关键词： Object detection

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Cramér-Rao bounds of near-field positioning based on electromagnetic propagation model

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IEEE Transactions on Vehicular technology 2023年第11期72卷 13808-13825页

作者： Chen, Ang Chen, Li Chen, Yunfei You, Changsheng Wei, Guo Yu, F. Richard University of Science and Technology of China CAS Key Laboratory of Wireless Optical Communication Hefei230027 China University of Durham Department of Engineering DurhamDH1 3LE United Kingdom Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen518055 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

The adoption of large-scale antenna arrays at high-frequency bands is widely envisioned in the beyond 5G wireless networks. This leads to the near-field regime where the wavefront is no longer planar but spherical, bringing new opportunities and challenges for communications and positioning. In this article, we improve the near-field positioning technology from the classical spherical wavefront model (SWM) to the more accurate and true electromagnetic propagation model (EPM). A generic near-field positioning model with different observation capabilities for three electric field types (vector, scalar, and overall scalar electric field) is developed based on the complete EPM. For these three observed electric field types, the Cramér-Rao bound (CRB) is adopted to evaluate the achievable estimation accuracy. The expressions of the CRBs for different electric field observations are derived by combining electromagnetic propagation concepts with estimation theory. Closed-form expressions can be further obtained as the terminal is assumed to be on the central perpendicular line (CPL) of the receiving antenna surface. Moreover, the above discussions are extended to the system with multiple receiving antennas. In this case, the CRBs using various electric field types are derived and the effect of different numbers of receiving antennas is deeply investigated. Numerical results are provided to quantify the CRBs and validate the analytical results. Also, the impact of different system parameters, including electric field type, wavelength, size of the receiving antenna, and number of antennas, is evaluated. © 1967-2012 IEEE.

关键词： Electric fields

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Root Pose Decomposition Towards Generic Non-rigid 3D Reconstruction with Monocular Videos

Root Pose Decomposition Towards Generic Non-rigid 3D Reconst...

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International Conference on computer Vision (ICCV)

作者： Yikai Wang Yinpeng Dong Fuchun Sun Xiao Yang Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology (BNRist) State Key Lab on Intelligent Technology and Systems Tsinghua University RealAI

This work focuses on the 3D reconstruction of non-rigid objects based on monocular RGB video sequences. Concretely, we aim at building high-fidelity models for generic object categories and casually captured scenes. To this end, we do not assume known root poses of objects, and do not utilize category-specific templates or dense pose priors. The key idea of our method, Root Pose Decomposition (RPD), is to maintain a per-frame root pose transformation, meanwhile building a dense field with local transformations to rectify the root pose. The optimization of local transformations is performed by point registration to the canonical space. We also adapt RPD to multi-object scenarios with object occlusions and individual differences. As a result, RPD allows non-rigid 3D reconstruction for complicated scenarios containing objects with large deformations, complex motion patterns, occlusions, and scale diversities of different individuals. Such a pipeline potentially scales to diverse sets of objects in the wild. We experimentally show that RPD surpasses state-of-the-art methods on the challenging DAVIS, OVIS, and AMA datasets. We provide video results in https://***.

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MMKE-BENCH: A MULTIMODAL EDITING BENCHMARK FOR DIVERSE VISUAL KNOWLEDGE

arXiv

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arXiv 2025年

作者： Du, Yuntao Jiang, Kailin Gao, Zhi Shi, Chenrui Zheng, Zilong Qi, Siyuan Li, Qing State Key Laboratory of General Artificial Intelligence BIGAI China Shandong University China University of Science and Technology of China China State Key Laboratory of General Artificial Intelligence Peking University China Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology China

Knowledge editing techniques have emerged as essential tools for updating the factual knowledge of large language models (LLMs) and multimodal models (LMMs), allowing them to correct outdated or inaccurate information without retraining from scratch. However, existing benchmarks for multimodal knowledge editing primarily focus on entity-level knowledge represented as simple triplets, which fail to capture the complexity of real-world multimodal information. To address this issue, we introduce MMKE-Bench, a comprehensive MultiModal Knowledge Editing Benchmark, designed to evaluate the ability of LMMs to edit diverse visual knowledge in real-world scenarios. MMKE-Bench addresses these limitations by incorporating three types of editing tasks: visual entity editing, visual semantic editing, and user-specific editing. Besides, MMKE-Bench uses free-form natural language to represent and edit knowledge, offering a more flexible and effective format. The benchmark consists of 2,940 pieces of knowledge and 8,363 images across 33 broad categories, with evaluation questions automatically generated and human-verified. We assess five state-of-the-art knowledge editing methods on three prominent LMMs, revealing that no method excels across all criteria, and that visual and user-specific edits are particularly challenging. MMKE-Bench sets a new standard for evaluating the robustness of multimodal knowledge editing techniques, driving progress in this rapidly evolving field. Copyright © 2025, The Authors. All rights reserved.

关键词： Semantics

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MACRO: Incentivizing Multi-Leader Game-Based Pareto-Efficient Crowdsourcing for Video Analytics 40

MACRO: Incentivizing Multi-Leader Game-Based Pareto-Efficien...

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40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Chen, Yu Zhang, Sheng Zhou, Ziying Wang, Xiaokun Liang, Yu Chen, Ning Yan, Yuting Xiao, Mingjun Wu, Jie Qian, Zhuzhong Xu, Harry Nanjing University State Key Lab. for Novel Software Technology China School of Systems Science Beijing Normal University China School of Computer and Electronic Information School of Artificial Intelligence Nanjing Normal University China School of Computer Science and Technology University of Science and Technology of China China Temple University Center for Networked Computing United States Samueli School of Engineering University of California Computer Science Department Los Angeles United States

ISBN: (纸本)9798350317152

In recent years, many crowdsourcing platforms have emerged, using the resources of recruited workers to perform diverse outsourcing tasks, where the video analytics attracts much attention due to its practical implications. For maximum profits, platforms carefully choose the workers and determine the video analytics configurations to ensure accuracy;meanwhile, workers possess the flexibility to tailor the configurations for their indivi-dual gains, which makes it hard for platforms to optimize their profits considering the platform-worker conflicts. In this paper, we design an incentive mechanism for Multi-leader game-based video Analytics upon CROwdsourcing, named MACRO, to over-come the above situation. Under that mechanism, we first formu-late the utility optimization problems for platforms and workers, respectively. We then propose a dual ascent-based method to op-timally determine the video analytics configurations for a multi-platform game, ensuring Pareto efficiency. Moreover, in the context of a multi-leader game involving platform-worker conflicts, we design an incentive function with its incentive factor update strategy and propose an ADMM-based approach for maximizing incentives that motivate workers to contribute to the platforms' profits. Rigorous proofs demonstrate the linear convergence of the MACRO to the multi-leader Stackelberg equilibrium. Trace-driven experiments show that MACRO improves the Pareto efficiency by 26.3%, outperforming other approaches. © 2024 IEEE.

关键词： Profitability

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INFLUENCE OF RECYCLED CONCRETE AGGREGATES ON THE ENGINEERING PROPERTIES OF ASPHALT: A CRITICAL REVIEW

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Indian Concrete Journal 2025年第3期99卷 44-59页

作者： Dagar, Lokesh Sahu, Vaishali Garg, Aman Department of Multidisciplinary Engineering The NorthCap University India NorthCap University Gurugram India State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology China

A significant quantity of debris from building and demolition is produced on a yearly basis in every region of the globe. The environmentally conscious and economically astute management of the debris left behind from building construction and demolition projects is a pressing subject. There have been several efforts in the past that have been made to utilize the debris from building and demolition in construction sector. These efforts have been made to either replace natural aggregates with coarse or fine aggregates using construction and demolition debris. Recent attempts have been made by the asphalt pavement industry to include trash from building and demolition in the form of recycled concrete aggregates. These recycled aggregates are meant to take the place of natural or virgin aggregates. This article provides a synopsis of the research that has been conducted by the researchers and published in a variety of countries throughout the globe. The current review article organizes the available research into categories according to the tests that were conducted as well as the significant results that were reported. In addition, a summary of the life cycle analysis and a forecast of the characteristics of asphalt mixes incorporating recycled concrete aggregates (RCA) is also included in this paper. In addition to the conclusion, this article also presents the research voids that still need to be filled. © 2025, Associated Cement Companies Ltd.. All rights reserved.

关键词： Construction industry

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Improved Particle Swarm Optimization Algorithm for EIT Image Reconstruction 20

Improved Particle Swarm Optimization Algorithm for EIT Image...

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20th International Multi-Conference on systems, Signals and Devices, SSD 2023

作者： Kahouli, Oumayma Hafsa, Mariem Hellara, Hiba Bennour, Imed Eddine Essoukri Ben Amarax, Najoua Kanoun, Olfa University of Sousse National Engineering School of Sousse Department of Computer Science Sousse4023 Tunisia National Engineering School of Sousse Laboratory of Advanced Technology and Intelligent Systems Tunisia Technische Universität Chemnitz Laboratory of Measurement and Sensor Technology Chemnitz Germany University of Sfax Laboratory of Signals Systems Artificial Intelligence and Networks Digital Research Center of Sfax Tunisia

ISBN: (纸本)9798350332568

Electrical Impedance Tomography (EIT) is a clinical imaging technique that gained a lot of attention because it is a non-invasive and radiation-free method. To obtain an inner image of the domain under study, a specific number of electrodes is attached to the surface of the object, then through a pair of electrodes, a low alternative current is injected. Potentials produced by this injection are measured with the remaining electrodes. Based on these boundary voltages measurements, the inner conductivity can be inferred, thus the image is reconstructed. The focus of this paper is to overcome the major weakness of the EIT image reconstruction technique, which is the low spatial resolution of the reconstructed images caused by the non-linearity of EIT inverse problem. This paper considers this problem, an optimization problem that is solved using the Particle Swarm Optimization (PSO) meta-heuristic. A variant of the standard PSO is proposed and validated, first on a circular mesh composed of 686 triangles then on a lung mesh composed of 2707 triangles. © 2023 IEEE.

关键词： Electrodes

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A Preliminary Study of Frequency Shift Mechanism in Magnetic Resonance Coupled Human Body Communication

A Preliminary Study of Frequency Shift Mechanism in Magnetic...

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2023 Cross Strait Radio science and Wireless technology Conference, CSRSWTC 2023

作者： Chen, Lina Wang, Jiamei Wei, Ziliang Pun, Sio Hang Vai, Mang I. Gao, Yueming College of Physics and Information Engineering Fuzhou University China Fuzhou University The International Joint Laboratory on Health Intelligent Monitoring Systems China University of Macau State Key Laboratory of Analog and Mixed-Signal VLSI China University of Macau Faculty of Science and Technology China

ISBN: (纸本)9798350358971

The Magnetic Resonance-Coupled Human Body Communication (MR-HBC) method presents advantages such as high path gain and enhanced information security, rendering it particularly suitable for establishing wireless body area networks. The optimal operation of MR-HBC relies on functioning at resonance frequency. However, owing to the intricate dielectric properties of human tissues and individual differences, the resonance frequency of communication systems frequently experiences varying degrees of deviation. To delve into the intrinsic mechanism behind frequency shifts, this paper establishes a finite element model based on the genuine dielectric properties and geometric structure of the human body. It investigates the augmentation effects of human tissue on MR-HBC, examines the influence of distinct tissue electrical properties on the electromagnetic field distribution of MR-HBC, and analyzes the inherent connection between frequency shifts and human tissue electrical characteristics. The results reveal that the electrical properties of human tissues stand as the primary factor affecting frequency shifts, with the extent of frequency deviation contingent upon the proportional composition of different tissues. © 2023 IEEE.

关键词： Electromagnetic simulation MR-HBC Resonance Frequency Shift

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AirVista: Empowering UAVs with 3D Spatial Reasoning Abilities Through a Multimodal Large Language Model Agent 27

AirVista: Empowering UAVs with 3D Spatial Reasoning Abilitie...

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27th IEEE International Conference on intelligent Transportation systems, ITSC 2024

作者： Lin, Fei Tian, Yonglin Wang, Yunzhe Zhang, Tengchao Zhang, Xinyuan Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Capital University of Economics and Business Beijing100070 China University of Chinese Academy of Sciences Department of Artificial Intelligence Beijing100049 China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Department of Engineering Science 999078 China

ISBN: (纸本)9798331505929

In urban environments, complex transportation demands, including land, air, and maritime transport, are increasingly growing. While significant advancements have been made in land transportation and autonomous driving, research on urban air mobility (UAM) systems is still in its early stages. This paper presents an innovative urban air unmanned aerial vehicle (UAV) framework: AirVista, which is designed and built based on the Artificial systems, Computational experiments, and Parallel execution (ACP) approach, integrated with a multimodal large language model (MLLM) agent. Considering that UAM tasks often require UAVs to possess fine-grained spatial perception and reasoning capabilities, and given that existing MLLMs are somewhat lacking in exploring 3D spaces, this paper further proposes an instruction fine-tuning strategy integrated with 3D spatial knowledge, which has been validated experimentally for its effectiveness. Additionally, to enhance the understanding of the efficiency of MLLM for UAV tasks, this paper delves into prompt fine-tuning templates tailored for UAV task decomposition. Through experimental demonstrations, we showcase that the prompt-tuned MLLM exhibits efficient task decomposition and execution capabilities in handling complex UAV tasks. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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An Analog Front-End with Automatic Gain Control for Galvanic-Coupled Human Body Communication

An Analog Front-End with Automatic Gain Control for Galvanic...

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2023 Cross Strait Radio science and Wireless technology Conference, CSRSWTC 2023

作者： Zhao, Wenxiang Li, Dongming Wang, Jiamei Pun, Sio Hang Vai, Mang I. Gao, Yueming College of Physics and Information Engineering Fuzhou University China Fuzhou University The International Joint Laboratory on Health Intelligent Monitoring Systems China University of Macau State Key Laboratory of Analog and Mixed-Signal VLSI China Faculty of Science and Technology University of Macau China

ISBN: (纸本)9798350358971

The channel loss of galvanic-coupled human body communication (GC-HBC) is greatly affected by human body activities or individual differences, which will cause large changes in the amplitude of the input signal received by the receiver. This requires the analog front-end to have the ability to adaptively adjust the circuit gain to ensure stable output of the amplified signal. In this regard, this paper proposes an analog front-end with automatic gain control for GC-HBC. This circuit uses a differential preamplifier circuit with high input impedance and a rear-stage automatic gain control circuit that uses voltage feedback to control gain. While achieving amplification of weak signals, it also meets the requirements for stable signal output. The measurement results show that it has an input impedance of > 100 M Ω, a maximum gain of 74dB, and a sensitivity of - 76dBm, effectively meeting the needs for capturing and amplifying weak signals. The loop stabilization time is 156μs, and the input dynamic range is 34dB, which can ensure stable output of the amplified signal amplitude when the input signal amplitude changes. © 2023 IEEE.

关键词： analog front-end automatic gain control GC-HBC stable output

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