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2023 SIGGRAPH Asia 2023 XR, SA 2023

作者： Zhang, Xuanmiao Sun, Linqi Yan, Shuo School of New Media Arts and Design Beihang University Beijing China School of New Media Arts & Design Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing China

ISBN: (纸本)9798400703164

This project reconstructs and reproduces the ecological context of "NVSHU"culture in an immersive (virtual reality) VR experience. We explore interactive approaches of communication for this unique intangible heritage context. "NVSHU"amplifies the effectiveness of intangible cultural heritage (ICH) preservation through narrative interaction and virtual character popularization techniques, aiming to enhance audiences' experiential learning, and augment their sense of presence and immersion. © 2023 Owner/Author.

关键词： virtual reality

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Object-level Hyperspectral Target Detection Based on Spectral-Spatial Features Integrated YOLOv4-Tiny Network 2022

Object-level Hyperspectral Target Detection Based on Spectra...

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4th International Conference on Image, Video and Signal Processing, IVSP 2022

作者： Nie, Jinyan Guo, Jian Xu, Qizhi State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Mechatronical Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9781450387415

The spectral resolution and spatial resolution of hyperspectral remote sensing images are mutually limited. To keep the same signal-to-noise ratio, the spatial resolution will decrease when the spectral resolution improves. The targets in low-resolution hyperspectral image, such as airplanes, cars and ships, appear as several pixels or sub-pixels. Current hyperspectral target detection methods mainly focus on pixel-level targets, which process spectral information and simple neighbourhood-pixel-related information in a pixel-by-pixel detection strategy. The contribution of spatial features is limited, and it takes a long time to train and detect pixel-by-pixel. Inspired by the deep learning-based object detection technologies for RGB images, we designed a hyperspectral image target detection method based on spectral-spatial features integrated YOLOv4-tiny network (SS-YOLONet). The 3D hyperspectral images were directly sent to the detection network, their spectral information and complex spatial features were extracted by channel attention module, spatial attention module and 3D convolution. Considering the small size of targets such as airplanes, we extracted two shallow features for small-scale objects. In the experiment, we used the pansharpened EO-1 hyperspectral images to verify the effectiveness of the proposed algorithm. © 2022 ACM.

关键词： Spectroscopy

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Boosting Document-Level Relation Extraction by Mining and Injecting Logical Rules

Boosting Document-Level Relation Extraction by Mining and In...

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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Fan, Shengda Mo, Shasha Niu, Jianwei School of Cyber Science and Technology Beihang University Beijing100191 China Zhongguancun Laboratory Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

Document-level relation extraction (DocRE) aims at extracting relations of all entity pairs in a document. A key challenge to DocRE lies in the complex interdependency between the relations of entity pairs. Unlike most prior efforts focusing on implicitly powerful representations, the recently proposed LogiRE (Ru et al., 2021) explicitly captures the interdependency by learning logical rules. However, LogiRE requires extra parameterized modules to reason merely after training backbones, and this disjointed optimization of backbones and extra modules may lead to sub-optimal results. In this paper, we propose MILR, a logic enhanced framework that boosts DocRE by Mining and Injecting Logical Rules. MILR first mines logical rules from annotations based on frequencies. Then in training, consistency regularization is leveraged as an auxiliary loss to penalize instances that violate mined rules. Finally, MILR infers from a global perspective based on integer programming. Compared with LogiRE, MILR does not introduce extra parameters and injects logical rules during both training and inference. Extensive experiments on two benchmarks demonstrate that MILR not only improves the relation extraction performance (1.1%-3.8% F1) but also makes predictions more logically consistent (over 4.5% Logic). More importantly, MILR also consistently outperforms LogiRE on both counts. Code is available at https://***/XingYing-stack/MILR. © 2022 Association for Computational Linguistics.

关键词： Integer programming

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Deblurring Neural Radiance Fields with Event-driven Bundle Adjustment

arXiv

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arXiv 2024年

作者： Qi, Yunshan Zhu, Lin Zhao, Yifan Bao, Nan Li, Jia State Key Laboratory of Virtual Reality Technology and Systems SCSE Beihang University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

Neural Radiance Fields (NeRF) achieves impressive 3D representation learning and novel view synthesis results with high-quality multi-view images as input. However, motion blur in images often occurs in low-light and high-speed motion scenes, which significantly degrades the reconstruction quality of NeRF. Previous deblurring NeRF methods struggle to estimate pose and lighting changes during the exposure time, making them unable to accurately model the motion blur. The bio-inspired event camera measuring intensity changes with high temporal resolution makes up this information deficiency. In this paper, we propose Event-driven Bundle Adjustment for Deblurring Neural Radiance Fields (EBAD-NeRF) to jointly optimize the learnable poses and NeRF parameters by leveraging the hybrid event-RGB data. An intensity-change-metric event loss and a photo-metric blur loss are introduced to strengthen the explicit modeling of camera motion blur. Experiments on both synthetic and real-captured data demonstrate that EBAD-NeRF can obtain accurate camera trajectory during the exposure time and learn a sharper 3D representations compared to prior works. Copyright © 2024, The Authors. All rights reserved.

关键词： 3D modeling

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Gaze Pattern Genius: Gaze-Driven VR Interaction Using Unsupervised Domain Adaption

Gaze Pattern Genius: Gaze-Driven VR Interaction Using Unsupe...

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virtual reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Kexin Wang Yang Gao Wenfeng Song Yuecheng Li Aimin Hao State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Computer School Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798350374490

ISBN: (纸本)9798350374506

This research advocates shifting VR interaction to gaze-driven interaction, a more intuitive alternative to traditional controls like VR controllers or gestures. Our focus is on enhancing neural network recognition accuracy, especially with limited user-specific gaze data. We introduce a novel framework for capturing gaze gesture patterns and propose a template dataset concept to boost neural training. Our unsupervised domain adaptation model, blending template depth and sparse user data authenticity, consistently excels in recognizing gaze patterns across diverse users. Rigorous benchmarking against leading architectures consistently shows our method outperforming. Empirical user studies confirm: gaze-driven interactions not only elevate VR experiences but also redefine immersive VR control dynamics.

关键词： Training Adaptation models Three-dimensional displays Conferences Neural networks virtual reality User interfaces

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AdaLog: Post-Training Quantization for Vision Transformers with Adaptive Logarithm Quantizer

arXiv

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arXiv 2024年

作者： Wu, Zhuguanyu Chen, Jiaxin Zhong, Hanwen Huang, Di Wang, Yunhong State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China School of Computer Science and Engineering Beihang University Beijing China

Vision Transformer (ViT) has become one of the most prevailing fundamental backbone networks in the computer vision community. Despite the high accuracy, deploying it in real applications raises critical challenges including the high computational cost and inference latency. Recently, the post-training quantization (PTQ) technique has emerged as a promising way to enhance ViT's efficiency. Nevertheless, existing PTQ approaches for ViT suffer from the inflexible quantization on the post-Softmax and post-GELU activations that obey the power-law-like distributions. To address these issues, we propose a novel non-uniform quantizer, dubbed the Adaptive Logarithm AdaLog (AdaLog) quantizer. It optimizes the logarithmic base to accommodate the power-law-like distribution of activations, while simultaneously allowing for hardware-friendly quantization and de-quantization. By employing the bias reparameterization, the AdaLog quantizer is applicable to both the post-Softmax and post-GELU activations. Moreover, we develop an efficient Fast Progressive Combining Search (FPCS) strategy to determine the optimal logarithm base for AdaLog, as well as the scaling factors and zero points for the uniform quantizers. Extensive experimental results on public benchmarks demonstrate the effectiveness of our approach for various ViT-based architectures and vision tasks including classification, object detection, and instance segmentation. Code is available at https://***/GoatWu/AdaLog. Copyright © 2024, The Authors. All rights reserved.

关键词： Chemical activation

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Research on ABAQUS-Based Fairing Mechanical Specimen Modeling and Mechanical Properties 7th

Research on ABAQUS-Based Fairing Mechanical Specimen Modelin...

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7th China Aeronautical science and technology Conference, CASTC 2024

作者： Dong, Yushuang Yin, Rongying Xin, Yuhan Yang, Shangru Gao, Hanjun School of Technology Beijing Forestry University Beijing100083 China AVIC HARBN AIRCRAFT INDUSTRY GROUP CO. LTD Harbin150060 China State Key Laboratory of Virtual Reality Technology and Systems School of Mechanical Engineering and Automation Beihang University Beijing100191 China

ISBN: (纸本)9789819797646

To deeply study the mechanical properties of the fairing, the mechanically cut specimens of the fairing were modeled and simulated using ABAQUS 6.14 finite element software. By establishing the geometry of the fairing mechanical specimens, the stress–strain response and deformation characteristics of six mechanical specimens under different loading conditions were simulated and analyzed. The results show the differences in the mechanical properties of the fairing specimens with two different materials, Notably, when aramid paper honeycomb material was juxtaposed with high-temperature fireproof cloth material, the former exhibited superior load-bearing capacity and robustness. In addition, the mechanical properties of the fairing were further investigated in depth by comparing the mechanical responses of the specimens under different gradient forces. © Chinese Society of Aeronautics and Astronautics 2025.

关键词： ABAQUS

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Exploring 3D Interaction with Gaze Guidance in Augmented reality

Exploring 3D Interaction with Gaze Guidance in Augmented Rea...

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IEEE Annual International Symposium virtual reality

作者： Yiwei Bao Jiaxi Wang Zhimin Wang Feng Lu State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China

Recent research based on hand-eye coordination has shown that gaze could improve object selection and translation experience under certain scenarios in AR. However, several limitations still exist. Specifically, we investigate whether gaze could help object selection with heavy 3D occlusions and help 3D object translation in the depth dimension. In addition, we also investigate the possibility of reducing the gaze calibration burden before use. Therefore, we develop new methods with proper gaze guidance for 3D interaction in AR, and also an implicit online calibration method. We conduct two user studies to evaluate different interaction methods and the results show that our methods not only improve the effectiveness of occluded objects selection but also alleviate the arm fatigue problem significantly in the depth translation task. We also evaluate the proposed implicit online calibration method and find its accuracy comparable to standard 9 points explicit calibration, which makes a step towards practical use in the real world.

关键词： Three-dimensional displays Design methodology Estimation User interfaces Fatigue Calibration Task analysis

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Prescribed Performance Evolution Control for VTOL UAVs Tracking a Moving Ship

Prescribed Performance Evolution Control for VTOL UAVs Track...

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International Conference on Control and Automation (ICCA)

作者： Yang Yuan Chen Wei Haibin Duan State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

An output constrained control method for the vertical take-off and landing (VTOL) unmanned aerial vehicles (DAVs) tracking a moving ship is proposed in this paper. The evolution path theory is introduced to narrow down the convergence region of the prescribed performance control (PPC) to obtain better dynamic performance. In addition, the fixed-time observer is adopted to deal with the external disturbance and actuator failure, and the fixed-time filter is used as reference model. The stability of the proposed method is verified by the Lyapunov function, and the comparative simulation has exhibited its superiority.

关键词： Actuators Simulation Observers Autonomous aerial vehicles Stability analysis Filtering theory Marine vehicles

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Semantics-Aware Avatar Locomotion Adaption for Indoor Cross-Scene AR Telepresence

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IEEE Transactions on Visualization and computer Graphics 2025年 PP卷 PP页

作者： Li, Yi-Jun Yang, Hao-Zhong Shu, Wen-Tong Wang, Miao Tsinghua University Department of Computer Science and Technology Beijing100084 China Beihang University China Beihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beijing100191 China Zhongguancun Laboratory Beijing100094 China

Geographically dispersed users often rely on virtual avatars as intermediaries to facilitate interactive communication and collaboration. However, existing methods for augmented reality (AR) telepresence applications exhibit limitations, including restricted movement within confined sub-areas, lack of smooth transitions, and the necessity for manually establishing object mapping between dissimilar environments. We present a novel interactive AR framework for virtual avatar locomotion adaption while preserving semantic coherence across dissimilar indoor scenes. Initially, we conduct a preliminary user study to identify key attributes influencing preferred avatar movement. These attributes are quantified as features, and a dataset of user annotations on avatar movements is created. Based on the user interaction and scene configurations, we employ a deep reinforcement learning neural network to guide the avatar to the ideal position while maximizing semantic coherence. We validate our proposed framework through simulations and user studies by implementing an AR-based 3D telepresence prototype, demonstrating the efficacy of our framework in conveying user intentions across dissimilar environments, enabling natural and immersive 3D telepresence interactions. © 1995-2012 IEEE.

关键词： Reinforcement learning

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