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Asymmetric Dual-Stream Networks for Lightweight RGB-D Salient Object Detection

Journal of Shanghai Jiaotong University (Science) 2025年 1-11页

作者： Wang, Yan Zheng, Wanlu Xia, Yaozheng Wang, Shaorong School of Information Science and Technology Beijing Forest University Beijing100083 China Engineering Research Center for Forestry-oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing100083 China Beijing Virtual Simulation and Visualization Engineering Center Beijing100871 China

Integrating image and depth information for RGB-D salient object detection has become a research hotspot in the field of saliency detection. Balancing the efficiency and performance of salient object detection models under resource constraints is a key challenge. To address this, this paper proposes an asymmetric lightweight network suitable for real-time RGB-D salient object detection tasks. The network reduces the number of network parameters by designing different lightweight feature extraction networks for different input modalities. Additionally, a multi-modal feature enhancement fusion module is designed to effectively fuse multi-modal features while compensating for the information loss caused by the lightweight backbone network. Moreover, this paper utilizes a global context module for dense decoding, aggregating local and global information of multi-scale features without significantly increasing computational complexity. The experimental results on five benchmarks show that the proposed lightweight RGB-D salient object detection network not only outperforms most mainstream models quantitatively and qualitatively, but also significantly outperforms other models in terms of efficiency, only with a parameter count of 5.1 million and a computational load of 0.77 gigaflops. This achievement validates the proposed method’s ability to achieve lightweight salient object detection while maintaining high efficiency. © Shanghai Jiao Tong University 2024.

关键词： Object recognition

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Passive activity enhances residual control ability in patients with complete spinal cord injury

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Neural Regeneration research 2025年第8期20卷 2337-2347页

作者： Yanqing Xiao Mingming Gao Zejia He Jia Zheng Hongming Bai Jia-Sheng Rao Guiyun Song Wei Song Xiaoguang Li Beijing Key Laboratory for Biomaterials and Neural Regeneration Beijing Advanced Innovation Center for Biomedical EngineeringSchool of Biological Science and Medical EngineeringBeihang UniversityBeijingChina Department of Rehabilitation Evaluation China Rehabilitation Research CenterBeijingChina Cardiac Center Beijing Children’s HospitalCapital Medical UniversityBeijingChina The State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijingChina Department of Rehabilitation Engineering China Rehabilitation Science InstituteBeijingChina

Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury ***,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface *** this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord *** patients with chronic complete thoracic spinal cord injury were *** electromyography data from eight major leg muscles were acquired and compared before and after the passive activity *** results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of *** the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically *** findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.

关键词： complete spinal cord injury cycle training epidural electrical stimulation motor training passive activity physiological state spinal cord circuit surface electromyography volitional control task

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AMIS: An Audiovisual Dataset for Multimodal XR research 25

AMIS: An Audiovisual Dataset for Multimodal XR Research

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Proceedings of the 16th ACM Multimedia Systems Conference

作者： Abhinav Bhattacharya Luís Fernando de Souza Cardoso Andy Schleising Gareth Rendle Adrian Kreskowski Felix Immohr Rakesh Rao Ramachandra Rao Wolfgang Broll Alexander Raake Audiovisual Technology Group TU Ilmenau Germany Ilmenau Germany Virtual Worlds and Digital Games Group TU Ilmenau Germany Ilmenau Germany Virtual Reality and Visualization Research Group Bauhaus-Universität Weimar Germany Weimar Germany

ISBN: (纸本)9798400714672

The Audiovisual Multimodal Interaction Suite (AMIS) is an open-source dataset and accompanying Unity-based demo implementation designed to aid research on immersive media communication and social XR environments. AMIS features synchronized audiovisual recordings of three actors performing monologues and participating in dyadic conversations across four modalities: talking-head videos, full-body videos, volumetric avatars, and personalized animated avatars. These recordings can be used to simulate scenarios such as traditional video conferences or XR meetings with 3D avatars in controlled and replicable environments. The limitations of existing datasets, which include a restricted number of audiovisual formats, a narrow application focus, and suboptimal inclusion of verbal and non-verbal cues, are addressed by AMIS. With AMIS Studio, a Unity-based demonstrator, researchers can explore the recordings and compare the different audiovisual formats in VR scenes. This paper outlines the creation of AMIS, its design considerations, and how it may be applied in interdisciplinary domains, including cognitive psychology, audiovisual quality assessment, and social XR research.

关键词： audiovisual dataset

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Open Source Metaverse Platform System for Educational Engagements and research Activities Using Layered Multicast Method

Open Source Metaverse Platform System for Educational Engage...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Kenichiro Ito Yong-Hao Hu Ayumi Igarashi Information Technology Center The University of Tokyo Tokyo Japan Virtual Reality Educational Research Center The University of Tokyo Tokyo Japan Graduate School of Medicine The University of Tokyo Tokyo Japan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

This paper introduce “chutvrc,” a web-based open-source metaverse platform system software designed to enhance educational engagements and research activities operable on various consumer devices. As a successor to Mozilla Hubs, chutvrc aims for high extensibility and customizability, specifically tailored to meet the needs of educational institutions and research communities. It is designed to be accessible from various devices and display environments, including VR equipment, PCs, smartphones, and tablets, ensuring broad interconnectivity and interoperability within the metaverse. A unique feature of chutvrc is its layered multicast teaching/speaking functionality, which allows for seamless educational sessions across multiple virtual rooms, enhancing the collaborative and interactive experience for educators and learners. Fully open source, chutvrc includes the client, server, protocol, and component software, benefiting educators and researchers by preserving all components of the virtual environment. This comprehensive open-source approach supports research replication and the management of 3D research data, enabling reanalysis and further contributing to the academic and research community.

关键词： Three-dimensional displays Protocols Metaverse User experience Extensibility System software Servers Smart phones Interoperability Consumer electronics

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Enhancing the Reconstruction from Non-uniform Point Sets Using Persistence Information

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4th Annual International Workshop on Computational Topology in Image Context (CTIC)

作者： Vucini, Erald VRVis Center for Virtual Reality and Visualization Research Austria

ISBN: (纸本)9783642302374;9783642302381

In this paper we propose an efficient method for selecting the reconstruction resolution of non-uniform representations. We analyze the topological difference between reconstructions based on Topological Persistence information and define a distance for quantifying such information. We compute the Persistence information with a state-of-the-art method and report in detail the characteristics of the proposed algorithm. We evaluate our method in different scenarios and compare to previous contributions. Our proposed method offers faster and more reliable results in an effort to improve the reconstruction process and to reduce the necessity for visual inspection.

关键词： Reconstruction Topology Persistence Bottleneck Distance

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Entropy-Optimized Texture Models

Entropy-Optimized Texture Models

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11th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2008)

作者： Zambal, Sebastian Buehler, Katja Hladuvka, Jiri VRVis Research Center for Virtual Reality and Visualization Austria

ISBN: (纸本)9783540859895

In order to robustly match a statistical model of shape and appearance (e.g. AAM) to an unseen image, it is crucial to employ a robust model fittness measure. Dense sampling of texture over the region covered by the shape of interest makes comparison of model and image in principle robust. However, when merely texture differences are taken into account, problems with low contrast regions, fuzzy features, global intensity variations, and irregularly varying structures occur. In this paper we introduce a novel entropy-optimized texture model (ETM). We map gray values of training images such that pixels represent, anatomical structures optimally in terms of information entropy. We match the ETM to unseen images employing Bayes' law. We validate our approach using four training sets (hearts in basal region, hearts in mid region, brain ventricles, and lumbar vertebrae) and conclude that ETMs perform better than AAMs. Not, only they reduce the average point-to-contour error, they are better suited to cope with large texture variances due to different, scanners and even modalities.

关键词： Medical imaging

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Fast and memory efficient feature detection using multiresolution probabilistic boosting trees

Fast and memory efficient feature detection using multiresol...

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19th International Conference in Central Europe on Computer Graphics, visualization and Computer Vision, WSCG 2011

作者： Schulze, Florian Major, David Bühler, Katja VRVis Center for Virtual Reality and Visualization Research Austria

ISBN: (纸本)9788086943831

This paper presents a highly optimized algorithm for fast feature detection in 3D volumes. Rapid detection of structures and landmarks in medical 3D image data is a key component for many medical applications. To obtain a fast and memory efficient classifier, we introduce probabilistic boosting trees (PBT) with partial cascading and classifier sorting. The extended PBT is integrated into a multiresolution scheme, in order to improve performance and works on block cache data structure which optimizes the memory footprint. We tested our framework on real world clinical datasets and showed that classical PBT can be significantly speeded up even in an environment with limited memory resources using the proposed optimizations.

关键词： Decision trees

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From pixels to buildings 7

From pixels to buildings

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7th Symposium on Remote Sensing: From Pixels to Processes 2006

作者： Gruber-Geymayer, B.C. Zebedin, L. Karner, K. VRVis Research Center for Virtual Reality and Visualization Graz Austria

This paper describes the land use classification of multispectral digital aerial images, the removal of buildings from the digital surface model and the visualization of the textured digital surface model with reconstructed buildings. The proposed approach applies spectral classification techniques to multispectral digital aerial images with RGB and NIR channels. The results of the land use classification are used both in dense matching and building extraction. Dense matching uses the knowledge of water areas to prevent wrong matches due to non-Lambertian reflections. The obtained digital surface model is used to generate the corresponding RGB ortho images. Further, in building extraction the classification is used as starting point for searching exact building borders and textures for building facades. The buildings in the digital surface model are replaced by refined building models using feature information. Results from a huge test area in city center of Graz are presented and analyzed. This approach produces automatically appealing visualization after a short interactive training phase for classification. © 2006 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Buildings

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Efficient edge matching using improved hierarchical chamfer matching

Efficient edge matching using improved hierarchical chamfer ...

引用

2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009

作者： Qiang, Zhang Pengfei, Xu Wen, Li Zhongke, Wu Mingquan, Zhou Research Center for Virtual Reality and Visualization Technology Beijing Normal University 100875 China

ISBN: (纸本)9781424438280

Matching is a central problem in pattern recognition and computer vision, its applications includes object detection and tracking. HCMA (hierarchical chamfer matching) is a classical image matching algorithm, which utilizes the edge information to match the images robustly and the multi-resolution pyramid to accelerate the matching process. However, for images with cluttered background and high resolution, HCMA is relatively computationally expensive, which has impeded its success in practical applications, especially in real-time applications. In this paper, an improved hierarchical chamfer matching algorithm is proposed to reduce its computational cost without degrading its matching quality. According to the experimental results, the proposed improvements are able to save 75% ∼ 95% of the computational time, without causing any false matching. ©2009 IEEE.

关键词： Object detection

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Interactive diffusion-based segmentation of volume data on graphics hardware 1

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2005 - Workshop on Image Processing for Medicine: Algorithms - Systems - Applications, BVM 2005

作者： Langer, Caroline Hadwiger, Markus Bühler, Katja Medical Visualization VRVis Research Center for Virtual Reality and Visualization A-1220 Wien Austria

Im vorliegenden Artikel wird ein verbesserter Ansatz für eine interaktive Segmentierung von Volumendaten auf Standard PCs vorgestellt. Sowohl Visualisierung als auch Segmentierung wurden durch Programmierung hand...

ISBN: (数字)9783540264316

ISBN: (纸本)3540250522

Im vorliegenden Artikel wird ein verbesserter Ansatz für eine interaktive Segmentierung von Volumendaten auf Standard PCs vorgestellt. Sowohl Visualisierung als auch Segmentierung wurden durch Programmierung handelsüblicher 3D Grafikkarten so stark beschleunigt, dass eine Darstellung des Fortschrittes der Segmentierung in Echtzeit und im Kontext des gesamten Datensatzes möglich ist. Dadurch kann direkt korrigierend in den Ablauf der Segmentierung eingegriffen werden. Der implementierte Segmentierungsalgorithmus kombiniert Region Growing (Bereichswachstumsverfahren) mit diffusionsbasierter Kantenerkennung und läßt sich durch Parametereinstellungen auf eine Vielzahl von Problemstellungen anwenden.

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