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RMGNet: The Progressive Relationship-Mining Graph Neural Network for Text-to-Image Person Re-Identification

IEEE Transactions on Circuits and systems for Video technology 2025年第6期35卷 5749-5761页

作者： Zhang, Xin Liu, Kun Wang, Xinwang Zhou, Zhong Chen, Haiyong Hebei University of Technology School of Artificial Intelligence Tianjin300130 China Southeast University School of Instrument Science and Engineering Jiangsu Nanjing210018 China Wuxi Institute of Technology School of Integrated Circuit Wuxi214121 China Zhongguancun Laboratory Beijing100086 China Beihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beijing100191 China

The Text-to-Image Person Re-identification (TI-ReID) task objective is to precisely identify the person’s images with the textual description of the person. The mainstream research methods focus on cross-modal aligning local features, and overlook the learning of intra-modal and cross-modal relationships between different features. This renders the person features lacking in high-level semantic information. To resolve such issues, we propose the Progressive Relationship-Mining Graph Network (RMGNet), including the Intra-Modal Relationship-Mining (IMRM) and the Cross-Modal Relationship-Mining (CMRM) module. These modules are employed to model and mine semantic relationship information among different features. Specifically, the IMRM module models and mines the high-level semantic interrelationships inherent in the image and text features. The CMRM module introduces the nearest neighbor method to model cross-modal semantic relationships to enhance the cross-modal semantic correspondence capabilities of person features. On this basis, we design the Adaptive Corner Center (Acc) loss and the Coarse-to-Fine Learning (C2FL) strategy. These ensure the network receives consistent and effective metric learning supervision throughout the entirety of the training process. To validate the efficacy of the proposed method, extensive experiments are conducted on three prevalent datasets: CHUK-PEDES, ICFC-PEDES, and RSTPReid. The achieved mAP of 70.59%, 41.62%, and 49.58% surpassed those current state-of-the-art methods. © 1991-2012 IEEE.

关键词： Graph neural networks

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PEIE: Physics Embedded Illumination Estimation for Adaptive Dehazing 39

PEIE: Physics Embedded Illumination Estimation for Adaptive ...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Liu, Huaizhuo Hu, Hai-Miao Jiang, Yonglong Liu, Yurui Hangzhou Innovation Institute Beihang University China State Key Laboratory of Virtual Reality Technology and Systems Beihang University China School of Computer Science and Engineering Beihang University China

ISBN: (纸本)157735897X

Deep learning-based methods have made significant progress in image dehazing. However, these methods often falter when applied to real-world hazy images, primarily due to the scarcity of paired real-world data and the limitations of current dehazing feature extractors. Toward these issues, we introduce a novel Physics Embedded Illumination Estimation (PEIE) method for adaptive real-world dehazing. Specifically, (1) we identify the limitations of the widely used Atmospheric Scattering Model and propose a new physical model, the Illumination-Adaptive Scattering Model (IASM), for more accurate illumination representation in hazy imaging;(2) we develop a robust data synthesis pipeline that leverages the physics embedded illumination estimation to generate realistic hazy images;and (3) we design an Illumination-Adaptive Dehazing Unit (IDU) to extract dehazing features consistent with our proposed IASM in the latent space. By integrating the IDU into a U-Net architecture to create IADNet, we achieve significant improvements in dehazing performance through end-to-end training on synthetic data. Extensive experiments validate the superior performance of our PEIE method, significantly surpassing the state-of-the-arts in real-world dehazing. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Deep learning

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RDM: A Light Field Super-Resolution Model Improved with Retinex Decomposition 16

RDM: A Light Field Super-Resolution Model Improved with Reti...

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16th International Conference on Signal Processing systems, ICSPS 2024

作者： Lyu, Wenqi Ke, Wei Sheng, Hao Ma, Xiao Liu, Lixue Faculty of Applied Sciences Macao Polytechnic University China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781510689251

Light field cameras hold significant value in applications such as depth estimation, 3D video acquisition, and image super-resolution. Compared to traditional single-image super-resolution methods, light field images can capture object information from multiple spatial and angular perspectives, which is more conducive to capturing detail information. However, current advanced light field super-resolution models still exhibit issues like blurriness, jaggedness, and dimness in 4x light field super-resolution. To address this, we propose a novel light field super-resolution framework that utilizes the Retinex decomposition concept to solve common problems such as ghosting and overlap, thereby improving image quality. By decomposing the light field image into illumination and reflection components and processing them separately, our model significantly enhances detail preservation and color consistency. Experimental results on multiple datasets demonstrate that our model exhibits outstanding performance, both subjectively and objectively, highlighting the effectiveness of this framework and its broad application potential in the field of computational imaging. © 2025 SPIE.

关键词： Image acquisition

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Holistic Correction with Object Prototype for Video Object Segmentation 39

Holistic Correction with Object Prototype for Video Object S...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Qiao, Shengye Xia, Changqun Liang, Yanjie Lan, Gongjin Li, Jia State Key Laboratory of Virtual Reality Technology and Systems SCSE Beihang University Beijing China Pengcheng Laboratory Shenzhen China Department of Computer Science and Technology Southern University of Science and Technology Shenzhen China

ISBN: (纸本)157735897X

Recently, memory-based methods have achieved progress in semi-supervised video object segmentation. However, these methods still suffer from unstructured challenges, such as object transformations, occlusions and disappearance-reappearance. To this end, we propose a Holistic Correction Network (HCNet) to adaptively acquire concise object prototypes for holistic correction at semantic, spatial and temporal aspects. Specifically, an Adaptive Prototype Update module is firstly designed to construct multi-level core object representations by associating object variations in consecutive frames with segmentation quality assessment. Based on the updated object prototypes, Semantic, Spatial and Temporal Correction modules are respectively designed to enhance the object semantics in the entire frame, eliminate the incorrect semantic enhancement outside the object regions and calibrate the estimated object regions with temporal changes of objects. Through the holistic correction mechanism with effective object prototypes, our proposed HCNet can robustly and efficiently deal with diverse complex scenarios. Extensive and comprehensive experiments conducted on seven datasets demonstrate that our proposed HCNet can significantly improve the segmentation performance. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Semantic Segmentation

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GooDFlight: Goal-Oriented Diffusion Model for Flight Trajectory Prediction

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IEEE Transactions on Aerospace and Electronic systems 2025年第3期61卷 7447-7465页

作者： Yang, Songru Liu, Liqin Chen, Bowen Cheng, Shaoyuan Shi, Zhenwei Zou, Zhengxia Beihang University School of Astronautics State Key Laboratory of Virtual Reality Technology and Systems Department of Aerospace Intelligent Science and Technology Beijing100191 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Beijing Institute of Space Mechanics and Electricity Beijing100076 China

Flight trajectory prediction is an essential task in the air traffic control field. Previous approaches to this problem usually follow a single-stage or short-term intention-guided prediction paradigm, which suffers from problems such as insufficient trajectory prediction diversity, limited accuracy, and interpretability. Different from existing paradigms, in this article, we present GooDFlight—A goal-oriented diffusion model for flight trajectory prediction. GooDFlight is a long-term intention-guided, diversity-emphasizing framework that decouples the flight trajectory prediction process into two stages: goal estimation and trajectory prediction. In the first stage, we propose a one-then-all goal estimation method to sufficiently cover the macro-uncertainty in flight patterns and then tailor the interaction-aware joint goal distribution, which extends the flight intention from a single, deterministic ground truth to the empirical intention distribution from the similar experience. In the second stage, we employ a transformer-based diffusion model to generate stochastic flight trajectories conditioned on the intention estimations, modeling the micro-uncertainty in flight operations under each pattern estimated in stage one. In terms of evaluation metrics, existing metrics have difficulties in accurately reflecting the model's ability to handle the natural uncertainty of trajectories. We further propose a simple yet effective global-local endpoints variance (GLeV) metric for evaluating the diversity of predicted trajectories under social acceptance. Our proposed method is validated in-depth on TrajAir, a large-scale dataset collected from the real-world air traffic control environment at the Pittsburgh-Butler Regional Airport, a nontowered general aviation airport. The experimental results demonstrate that the proposed method significantly outperforms other methods in terms of both accuracy and diversity with superior interpretability. © 1965-2011 IEEE.

关键词： Stochastic systems

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Long-term stress relaxation behaviors and mechanisms of 2219 Al-Cu alloy under various temperatures and initial stresses

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Journal of Materials science & technology 2024年第13期180卷 174-192页

作者： Hechuan Song Hanjun Gao Qingdong Zhang Xiaomin Zhou Boyang Zhang School of Mechanical Engineering University of Science and Technology BeijingBeijing 100083China Shunde Innovation School University of Science and Technology BeijingFoshan 528399China State Key Laboratory of Virtual Reality Technology and Systems&School of Mechanical Engineering and Automation Beihang UniversityBeijing 100191China Anhui Hengli Additive Manufacturing Technology Co. Ltd.Wuhu 241200China

Large 2219 Al-Cu alloy aerospace integral components suffer from long-term stress relaxation aging(SRA)due to complex temperature and stress loads during aging treatment/forming and service process,which makes it difficult to ensure their appropriate residual stress and excellent mechanical and service ***,the research is limited to a thorough understanding of macroscopic and microscopic features and underlying mechanisms of the long-term SRA under multivariable aging ***-fore,this study investigated macroscopic and microscopic features of long-term SRA under different tem-peratures(120 ℃ to 190 ℃),initial stress levels(100 MPa to 250 MPa)and durations(0 h to 50 h)through stress relaxation curves,metallographic traits,Vickers hardness,tensile performance,disloca-tions and phases of *** the basis of experimental outcomes,the comprehensive mecha-nisms beneath SRA were unraveled through dislocation theory,multiphase strengthening mechanisms and thermodynamics,where the interplays of stress relaxation behavior with age-hardening response were taken into *** results showed elevations in the rate of stress reduction as the tem-perature and initial stress *** an initial stress greater than the yield stress of alloy,a marked in-crease in stress relaxation was found,and the mechanisms transform from the intragranular motion of dislocations and diffusion of grain boundaries to the intragranular and intergranular motion of disloca-tions and migration of grain *** stress reduction rate rose sharply when the temperature exceeded 175 ℃,and the dislocation movement mechanisms transform from gliding to climbing of *** relaxation is in nature progressive transformation of strain from elastic into a permanently inelastic state via the motion of dislocations,leading to the decrease of movable dislocations and the increase of immovable dislocations with more stable *** age hardening i

关键词： 2219 aluminum alloys Stress relaxation aging Residual stresses Microstructures Dislocations Mechanisms

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Light field depth estimation:A comprehensive survey from principles to future

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High-Confidence Computing 2024年第1期4卷 92-107页

作者： Tun Wang Hao Sheng Rongshan Chen Da Yang Zhenglong Cui Sizhe Wang Ruixuan Cong Mingyuan Zhao State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Zhongfa Aviation Institute Beihang UniversityHangzhou 311115China Faculty of Applied Sciences Macao Polytechnic UniversityMacao 999078China State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Light Field(LF)depth estimation is an important research direction in the area of computer vision and computational photography,which aims to infer the depth information of different objects in threedimensional scenes by capturing LF *** this new era of significance,this article introduces a survey of the key concepts,methods,novel applications,and future trends in this *** summarize the LF depth estimation methods,which are usually based on the interaction of radiance from rays in all directions of the LF data,such as epipolar-plane,multi-view geometry,focal stack,and deep *** analyze the many challenges facing each of these approaches,including complex algorithms,large amounts of computation,and speed *** addition,this survey summarizes most of the currently available methods,conducts some comparative experiments,discusses the results,and investigates the novel directions in LF depth estimation.

关键词： Light field Depth estimation Deep learning Sub-aperture image Epipolar-plane image

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UAV swarm air combat maneuver decision-making method based on multi-agent reinforcement learning and transferring

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science China(Information sciences) 2024年第8期67卷 49-66页

作者： Zhiqiang ZHENG Chen WEI Haibin DUAN State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical Engineering Beihang University

During short-range air combat involving unmanned aircraft vehicle(UAV) swarms, UAVs must make accurate maneuver decisions based on information from both enemy and friendly UAVs. This dual requirement of competition and cooperation presents a significant challenge in the field of unmanned air combat. In this paper, a method based on multi-agent reinforcement learning(MARL) is proposed to address this issue. An actor network containing three subnetworks that can handle different types of situational information is designed. Hence, the results from simpler one-on-one scenarios are leveraged to enhance the complex swarm air combat training process. Separate state spaces for local and global information are designed for the actor and critic networks. A detailed reward function is proposed to encourage *** prevent lazy participants in air combat, a reward assignment operation is applied to distribute these dense rewards. Simulation testing and ablation experiments demonstrate that both the transfer operation and reward assignment operation can effectively deal with the swarm air combat scenario, and reflect the effectiveness of the proposed method.

关键词： UAV swarm short-range air combat multi-agent reinforcement learning reward assignment transfer

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Prescribed Performance Evolution Control for Quadrotor Autonomous Shipboard Landing

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1151-1162页

作者： Yang Yuan Haibin Duan Zhigang Zeng State Key Laboratory of Virtual Reality Technology and Systems the School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China State Key Laboratory of Virtual Reality Technology and Systems the School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083 Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China

The shipboard landing problem for a quadrotor is addressed in this paper,where the ship trajectory tracking control issue is transformed into a stabilization control issue by building a relative position *** guarantee both transient performance and steady-state landing error,a prescribed performance evolution control(PPEC)method is developed for the relative position *** addition,a novel compensation system is proposed to expand the performance boundaries when the input saturation occurs and the error exceeds the predefined *** the wind and wave on the relative position model,an adaptive sliding mode observer(ASMO)is designed for the disturbance with unknown upper *** on the dynamic surface control framework,a shipboard landing controller integrating PPEC and ASMO is established for the quadrotor,and the relative position control error is guaranteed to be uniformly ultimately *** results have verified the feasibility and effectiveness of the proposed shipboard landing control scheme.

关键词： error integrating stabilization

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VibroArm: Enhancing the Sensation of Forearm Deformation in virtual reality Using Vibrotactile Funneling Illusion 23

VibroArm: Enhancing the Sensation of Forearm Deformation in ...

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23rd IEEE International Symposium on Mixed and Augmented reality, ISMAR 2024

作者： Lin, Yilong Xie, Tianze Chang, Yingjie Luo, Hu Wang, Dangxiao Je, Seungwoo Southern University of Science and Technology School of Design China Beihang university State Key Lab of Virtual Reality Technology and Systems China

ISBN: (纸本)9798331516475

When we enter virtual reality (VR) in the first person, the avatar replaces our real body. Within a certain range of mismatches, we tend to identify with our avatar and perceive it as our own body. Previous research has shown that we can even believe that a deformed forearm is our own through haptic and visual feedback. However, the haptic devices used in earlier research were only explored using skin-stretching and weight-shifting. Vibrotactile feedback is the most common technique used to create a haptic VR experience in academia and industry because of its light weight and ease of application. Taking these advantages, we introduce VibroArm, a lightweight wearable haptic system with the vibrotactile funneling illusion that enhances the virtual forearm's ownership in the forearm deformation illusion. In a perceptual study, we determined that users can make correct direction judgments about vibration on the forearm in different directions. The result shows that all vibration patterns can be sufficiently recognized, with an average recognition rate of $87.17 \%$. Based on our results, we designed 18 vibration patterns and compared their impact on the forearm deformation illusion. Finally, our study shows that using VibroArm in VR applications can significantly improve user realism and enjoyment compared to relying on visual feedback alone. © 2024 IEEE.

关键词： virtual environments

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