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Unbounded-GS: Extending 3D Gaussian Splatting With Hybrid Representation for Unbounded Large-Scale Scene Reconstruction
Wanzhang Li;Fukun Yin;Wen Liu;Yiying Yang;Xin Chen;Biao Jiang;Gang Yu;Jiayuan Fan
Modeling large-scale scenes from multi-view images is challenging due to the trade-off dilemma between visual quality and computational cost. Existing NeRF-based methods have made advancements in neural implicit representation through volumetric ray-marching, but still struggle to deal with cubically growing sampling space in large-scale scenes. Fortunately, the rendering approach based on 3D Gaus...Show More
Enabling Trustable Financing: A Verifiable Privacy-Preserving Cross-Chain Protocol
Lidu Lou;Wenbin He;Xiangyun Tang;Yiying Yang;Tao Zhang;Yanyu Cheng;Cai Xu
2024 IEEE/CIC International Conference on Communications in China (ICCC Workshops)
Year: 2024 | Conference Paper |
Generative AI-enabled wireless communications enhance efficiency and offer new tools for supply chain finance (SCF) innovation. SCF optimizes capital efficiency and reduces risk, but information asymmetry hinders risk assessment. Blockchain technology addresses these challenges by solving information asymmetry and regulatory issues. However, issues of privacy protection, reliability, and traceabil...Show More
Progression Cognition Reinforcement Learning With Prioritized Experience for Multi-Vehicle Pursuit
Xinhang Li;Yiying Yang;Zheng Yuan;Zhe Wang;Qinwen Wang;Chen Xu;Lei Li;Jianhua He;Lin Zhang
Multi-vehicle pursuit (MVP) such as autonomous police vehicles pursuing suspects is important but very challenging due to its mission and safety-critical nature. While multi-agent reinforcement learning (MARL) algorithms have been proposed for MVP in structured grid-pattern roads, the existing algorithms use random training samples in centralized learning, which leads to homogeneous agents showing...Show More
Improvement by Monte Carlo for Trajectory Similarity-Based RUL Prediction
Trajectory similarity-based evaluation is the most intuitive method for remaining useful life (RUL) prediction when abundant run-to-failure data are available. However, practical scenarios often present a challenge with limited access to such trajectories. This article introduces an improved similarity-based method to bridge the gap by employing Monte Carlo to generate more trajectories. To begin,...Show More
An Opponent-Aware Reinforcement Learning Method for Team-to-Team Multi-Vehicle Pursuit via Maximizing Mutual Information Indicator
Qinwen Wang;Xinhang Li;Zheng Yuan;Yiying Yang;Chen Xu;Lin Zhang
2022 18th International Conference on Mobility, Sensing and Networking (MSN)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
The pursuit-evasion game in Smart City brings a profound impact on the Multi-vehicle Pursuit (MVP) problem, when police cars cooperatively pursue suspected vehicles. Existing studies on the MVP problems tend to set evading vehicles to move randomly or in a fixed prescribed route. The opponent modeling method has proven considerable promise in tackling the non-stationary caused by the adversary age...Show More
Graded-Q Reinforcement Learning with Information-Enhanced State Encoder for Hierarchical Collaborative Multi-Vehicle Pursuit
Yiying Yang;Xinhang Li;Zheng Yuan;Qinwen Wang;Chen Xu;Lin Zhang
2022 18th International Conference on Mobility, Sensing and Networking (MSN)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
The multi-vehicle pursuit (MVP), as a problem abstracted from various real-world scenarios, is becoming a hot research topic in the Intelligent Transportation System (ITS). The combination of Artificial Intelligence (AI) and connected vehicles has greatly promoted the research development of MVP. However, existing works on MVP pay little attention to the importance of information exchange and coop...Show More
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