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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Wang, Zhiyuan Meng, Qingkai Zhang, Shan Luo, Hongbin Beihang University School of Computer Science and Engineering Beijing China Beihang University State Key Laboratory of Virtual Reality Technology and Systems China Beihang University Institute of Artificial Intelligence Beijing China State Key Laboratory of Software Development Environment China

ISBN: (纸本)9798350334142

Many Internet platforms collect fresh information of various points of interest (PoIs) relying on users who happen to be nearby the PoIs. The platform will offer reward to incentivize users and compensate their costs incurred from information acquisition. In practice, the user cost (and its distribution) is hidden to the platform, thus it is challenging to determine the optimal reward. In this paper, we investigate how the platform dynamically rewards the users, aiming to jointly reduce the age of information (AoI) and the operational expenditure (OpEx). Due to the hidden cost distribution, this is an online non-convex learning problem with partial feedback. To overcome the challenge, we first design an age-based rewarding scheme, which decouples the OpEx from the unknown cost distribution and enables the platform to accurately control its OpEx. We then take advantage of the age-based rewarding scheme and propose an exponentially discretizing and learning (EDAL) policy for platform operation. We prove that the EDAL policy performs asymptotically as well as the optimal decision (derived based on the cost distribution). Simulation results show that the age-based rewarding scheme protects the platform's OpEx from the influence of the user characteristics, and verify the asymptotic optimality of the EDAL policy. © 2023 IEEE.

关键词： Simulation platform

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From Human Oral Instructions to General Representations of Knowledge: A New Paradigm for Industrial Robots Skill Teaching 6th

From Human Oral Instructions to General Representations of K...

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6th International Conference on Cognitive systems and Signal Processing, ICCSIP 2021

作者： Chen, Shiyu Zhao, Yongjia Lei, Xiaoyong Qi, Tao Liu, Kan State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Jiangxi Research Institute Beihang University Jiangxi Beijing China

ISBN: (纸本)9789811692468

Converting human oral instructions into general representations of knowledge which robots can understand, can realize more advanced behaviors for unmanned driving, drones, robots and other fields. This paper presents a novel paradigm based on two-stage structure that transforms human oral instructions into general representations of operating knowledge. Firstly, a Speech-to-Text module is used to realize automatic speech recognition, which results in a text expression for the input oral instruction. In the second stage, a Text-to-Knowledge module is used to realize natural language understanding, which introduces and visualizes task-related knowledge graphs converted from the text expression. To validate this paradigm, the task of computer motherboard assembly was chosen as an example, and a low-cost monophonic speech corpus named PC-CORPUS was built. This PC-CORPUS, is 3 h 44 min long and has 2278 wave audios. 14 speakers from different accent areas in China were invited in the recording. Then experiments were designed and carried out on this paradigm with PC-CORPUS. The average edit distance of this paradigm is 10.87%, comparing the triples of final visual knowledge representations with the ones were labeled by the experts. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Knowledge graph

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TopicDVC: Dense Video Captioning with Topic Guidance

TopicDVC: Dense Video Captioning with Topic Guidance

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Edge Computing and Scalable Cloud (EdgeCom), IEEE International Conference on

作者： Wei Chen State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China

ISBN: (数字)9798350377132

ISBN: (纸本)9798350377149

Dense video captioning involves detecting and describing multiple events within a video coherently. Events within a video typically share a common topic, and incorporating this topic information into the model can enhance the quality and coherence of the generated captions. However, existing dense video captioning datasets lack explicit topic annotations. To address this, we design a topic generator that utilizes a diffusion model with strong generative capabilities to generate topic information from a given video. During the training stage, we use the features of ground-truth captions as pseudo-topic labels. The video topics diffuse from the features of groundtruth captions to a random distribution, and the model learns to reverse this noising process conditioned on video features. During inference, the model iteratively denoises the Gaussian noise into topic features conditioned on video features. In this paper, we propose TopicDVC, a novel dense video captioning framework. TopicDVC applies the topic information generated by the topic generator to guide the model in generating more coherent captions. Experiments on the ActivityNet Captions dataset demonstrate that leveraging the topics generated by the diffusion model significantly improves the performance of dense video captioning, producing more accurate and coherent captions.

关键词： Training Accuracy Annotations Video description Gaussian noise Coherence Diffusion models

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"achi Mukua Experience Space"-A Multi-Player Immersive Experience of Yunnan ICH Dance 23

"achi Mukua Experience Space"-A Multi-Player Immersive Exper...

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2023 SIGGRAPH Asia 2023 Art Papers, SA 2023

作者： Luo, Siyu Yan, Shuo School of New Media Arts and Design Beihang University Beijing China School of New Media Arts and Design Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China

ISBN: (纸本)9798400703201

Increasingly, intangible cultural heritage (ICH) dance is being performed interactively through immersive experiences. However, these experiences often leaving participants isolated and lacking the connection to the cultural context of ICH dances. This project focuses on designing interactive mechanism that combine collaborative multi-players interactions with the collective nature of ICH dance. It explores the advantage of bio-signals as visual feedback in multi-player dance interactions. The project aims to create an immersive social space where participants can be fully immersed in the dance atmosphere and gain a deeper understanding of intangible heritage. © 2023 ACM.

关键词： Visual communication

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Robust Dual-Modal Speech keyword Spotting for XR Headsets

arXiv

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arXiv 2024年

作者： Cai, Zhuojiang Ma, Yuhan Lu, Feng State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China

While speech interaction finds widespread utility within the Extended reality (XR) domain, conventional vocal speech keyword spotting systems continue to grapple with formidable challenges, including suboptimal performance in noisy environments, impracticality in situations requiring silence, and susceptibility to inadvertent activations when others speak nearby. These challenges, however, can potentially be surmounted through the cost-effective fusion of voice and lip movement information. Consequently, we propose a novel vocal-echoic dual-modal keyword spotting system designed for XR headsets. We devise two different modal fusion approches and conduct experiments to test the system’s performance across diverse scenarios. The results show that our dual-modal system not only consistently outperforms its single-modal counterparts, demonstrating higher precision in both typical and noisy environments, but also excels in accurately identifying silent utterances. Furthermore, we have successfully applied the system in real-time demonstrations, achieving promising results. The code is available at https://***/caizhuojiang/VE-KWS. Copyright © 2024, The Authors. All rights reserved.

关键词： Cost effectiveness

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Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-rank Decomposition 24

Decoupling General and Personalized Knowledge in Federated L...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Wu, Xinghao Liu, Xuefeng Niu, Jianwei Wang, Haolin Tang, Shaojie Zhu, Guogang Su, Hao State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China Department of Management Science and Systems University at Buffalo BuffaloNY United States School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9798400706868

To address data heterogeneity, the key strategy of Personalized Federated Learning (PFL) is to decouple general knowledge (shared among clients) and client-specific knowledge, as the latter can have a negative impact on collaboration if not removed. Existing PFL methods primarily adopt a parameter partitioning approach, where the parameters of a model are designated as one of two types: parameters shared with other clients to extract general knowledge and parameters retained locally to learn client-specific knowledge. However, as these two types of parameters are put together like a jigsaw puzzle into a single model during the training process, each parameter may simultaneously absorb both general and client-specific knowledge, thus struggling to separate the two types of knowledge effectively. In this paper, we introduce FedDecomp, a simple but effective PFL paradigm that employs parameter additive decomposition to address this issue. Instead of assigning each parameter of a model as either a shared or personalized one, FedDecomp decomposes each parameter into the sum of two parameters: a shared one and a personalized one, thus achieving a more thorough decoupling of shared and personalized knowledge compared to the parameter partitioning method. In addition, as we find that retaining local knowledge of specific clients requires much lower model capacity compared with general knowledge across all clients, we let the matrix containing personalized parameters be low rank during the training process. Moreover, a new alternating training strategy is proposed to further improve the performance. Experimental results across multiple datasets and varying degrees of data heterogeneity demonstrate that FedDecomp outperforms state-of-the-art methods up to 4.9%. The code is available at https://***/XinghaoWu/FedDecomp © 2024 ACM.

关键词： Federated learning

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"embark the Journey · Embrace the Universe": An Interactive System of Astronomy Education Based on Spherical TUI in MR 23

"embark the Journey · Embrace the Universe": An Interactive...

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2023 SIGGRAPH Asia 2023 XR, SA 2023

作者： Liang, Xiaozhan Hu, Yong Shen, Xukun School of New Media Art and Design Beihang University Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Yunnan Innovation Institute of Beihang University Yunnan China

ISBN: (纸本)9798400703164

The widespread adoption and application of MR technology have opened up new possibilities in the field of education. Integrating physical objects and virtual contents in the physical interactive interface provides a larger practical platform for astronomy science education. However, very few attempts are currently at this form of science education. Therefore, we have summarized the design principles for the spherical TUI regarding both interactive interfaces and behaviors. Based on this, we have developed a spherical TUI-based astronomical knowledge system. It delivers users with a more diverse knowledge presentation by a fusion of virtual and reality and mapping interaction of spherical TUI in MR. © 2023 Owner/Author.

关键词： Spheres

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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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BakedAvatar: Baking Neural Fields for Real-Time Head Avatar Synthesis

arXiv

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arXiv 2023年

作者： Duan, Hao-Bin Wang, Miao Shi, Jin-Chuan Chen, Xu-Chuan Cao, Yan-Pei State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Zhongguancun Laboratory Beijing100191 China ARC Lab Tencent PCG Beijing China

Synthesizing photorealistic 4D human head avatars from videos is essential for VR/AR, telepresence, and video game applications. Although existing Neural Radiance Fields (NeRF)-based methods achieve high-fidelity results, the computational expense limits their use in real-time applications. To overcome this limitation, we introduce BakedAvatar, a novel representation for real-time neural head avatar synthesis, deployable in a standard polygon rasterization pipeline. Our approach extracts deformable multi-layer meshes from learned isosurfaces of the head and computes expression-, pose-, and view-dependent appearances that can be baked into static textures for efficient rasterization. We thus propose a three-stage pipeline for neural head avatar synthesis, which includes learning continuous deformation, manifold, and radiance fields, extracting layered meshes and textures, and fine-tuning texture details with differential rasterization. Experimental results demonstrate that our representation generates synthesis results of comparable quality to other state-of-the-art methods while significantly reducing the inference time required. We further showcase various head avatar synthesis results from monocular videos, including view synthesis, face reenactment, expression editing, and pose editing, all at interactive frame rates on commodity devices. Source codes and demos are available on our project page. © 2023, CC BY.

关键词： Textures

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IAACS: Image aesthetic assessment through color composition and space formation

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virtual reality & Intelligent Hardware 2023年第1期5卷 42-56页

作者： Bailin YANG Changrui ZHU Frederick WBLI Tianxiang WEI Xiaohui LIANG Qingxu WANG School of Computer and Information Engineering Zhejiang Gongshang UniversityHangzhou 310018China Department of Computer Science University of DurhamDH13LEUnited Kingdom College of Intelligence and Computing Tianjin UniversityTianjin 300072China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China

Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics of the general public. Although deep learning methods have successfully learned good visual features from images,correctly assessing the aesthetic quality of an image remains a challenge for deep learning. Methods To address this, we propose a novel multiview convolutional neural network to assess image aesthetics assessment through color composition and space formation(IAACS). Specifically, from different views of an image––including its key color components and their contributions, the image space formation, and the image itself––our network extracts the corresponding features through our proposed feature extraction module(FET) and the Image Net weight-based classification model. Result By fusing the extracted features, our network produces an accurate prediction score distribution for image aesthetics. The experimental results show that we have achieved superior performance.

关键词： Image aesthetic assessment Color composition Space formation Deep learning

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