自动驾驶

Guided Exploration of Human Intentions for Human-Robot Interaction

Min Chen, David Hsu, Wee Sun Lee

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.RO

Comments Appears at the 13th International Workshop on the Algorithmic Foundations of Robotics, 2018

Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation

Matthew O'Kelly, Aman Sinha, Hongseok Namkoong, John Duchi, Russ Tedrake

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.RO

Comments NeurIPS 2018

Monocular and Stereo Cues for Landing Zone Evaluation for Micro UAVs

Rohit Garg, Shichao Yang, Sebastian Scherer

专题命中 仿真评测 ：LiDAR(abstract)；分类 cs.RO

DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing

Xiaofei Xie, Lei Ma, Felix Juefei-Xu, Hongxu Chen, Minhui Xue, Bo Li, Yang Liu, Jianjun Zhao, Jianxiong Yin, Simon See

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.AI

Efficient Decentralized Deep Learning by Dynamic Model Averaging

Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.AI

Scientific image rendering for space scenes with the SurRender software

Roland Brochard, Jérémy Lebreton, Cyril Robin, Keyvan Kanani, Grégory Jonniaux, Aurore Masson, Noela Despré, Ahmad Berjaoui

专题命中 仿真评测 ：LiDAR(abstract)；分类 cs.CV

Comments 11 pages, 10 figures, 69th International Astronautical Congress (IAC), Bremen, Germany, 1-5 October 2018, https://www.airbus.com/space/space-exploration/SurRenderSoftware.html

Interest point detectors stability evaluation on ApolloScape dataset

Jacek Komorowski, Konrad Czarnota, Tomasz Trzcinski, Lukasz Dabala, Simon Lynen

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.CV

Evaluation of Neural Networks for Image Recognition Applications: Designing a 0-1 MILP Model of a CNN to create adversarials

Lucas Schelkes

专题命中 仿真评测 ：self-driving(abstract)；分类 cs.CV

Comments Thesis Bergische Universität Wuppertal

An Auto-tuning Framework for Autonomous Vehicles

Haoyang Fan, Zhongpu Xia, Changchun Liu, Yaqin Chen, Qi Kong

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.RO

Comments 7 pages, 9 figures, 2 tables

Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing

Jian Zhao, Jianshu Li, Yu Cheng, Li Zhou, Terence Sim, Shuicheng Yan, Jiashi Feng

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.CV

Comments The first three authors are with equal contributions

What Face and Body Shapes Can Tell About Height

Semih Günel, Helge Rhodin, Pascal Fua

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.CV

Sim4CV: A Photo-Realistic Simulator for Computer Vision Applications

Matthias Müller, Vincent Casser, Jean Lahoud, Neil Smith, Bernard Ghanem

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.CV

Comments Published at the International Journal of Computer Vision (IJCV), 2018

3D Registration of Aerial and Ground Robots for Disaster Response: An Evaluation of Features, Descriptors, and Transformation Estimation

Abel Gawel, Renaud Dubé, Hartmut Surmann, Juan Nieto, Roland Siegwart, Cesar Cadena

专题命中 仿真评测 ：LiDAR(abstract)；分类 cs.RO

Comments Awarded Best Paper at the 15th IEEE International Symposium on Safety, Security, and Rescue Robotics 2017 (SSRR 2017)

Human Pose Forecasting via Deep Markov Models

Sam Toyer, Anoop Cherian, Tengda Han, Stephen Gould

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.CV

Comments Accepted to DICTA'17

Momo: Monocular Motion Estimation on Manifolds

Johannes Graeter, Tobias Strauss, Martin Lauer

专题命中 仿真评测 ：autonomous driving(abstract)；分类 cs.CV

Maximum Resilience of Artificial Neural Networks

Chih-Hong Cheng, Georg Nührenberg, Harald Ruess

专题命中 仿真评测 ：self-driving(abstract)；分类 cs.AI

Comments Timestamp research work conducted in the project. version 2: fix some typos, rephrase the definition, and add some more existing work

Multisensory Omni-directional Long-term Place Recognition: Benchmark Dataset and Analysis

Ashwin Mathur, Fei Han, Hao Zhang

专题命中 仿真评测 ：self-driving(abstract)；分类 cs.RO

Comments 15 pages

MultiCol-SLAM - A Modular Real-Time Multi-Camera SLAM System

Steffen Urban, Stefan Hinz

专题命中 仿真评测 ：self-driving(abstract)；分类 cs.CV

Comments 15 pages, 8 figures, 2 tables

Human Arm simulation for interactive constrained environment design

Liang Ma, Ruina Ma, Damien Chablat, Fouad Bennis

专题命中 仿真评测 ：trajectory planning(abstract)；分类 cs.RO

Comments International Journal on Interactive Design and Manufacturing (IJIDeM) (2012) 1-12. arXiv admin note: substantial text overlap with arXiv:1012.4327

PIPE: Personalizing Recommendations via Partial Evaluation

Naren Ramakrishnan

专题命中 仿真评测 ：BEV(abstract)；分类 cs.AI

Revolutionizing Validation and Verification: Explainable Testing Methodologies for Intelligent Automotive Decision-Making Systems

Halit Eris, Stefan Wagner

专题命中 仿真评测 ：autonomous driving(abstract,journal_ref)

Comments Preprint to be published at SE4ADS

Journal ref 2025 IEEE/ACM 1st International Workshop on Software Engineering for Autonomous Driving Systems (SE4ADS), Ottawa, ON, Canada, 2025, pp. 34-37

DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place Recognition

Marvin Chancán, Michael Milford

专题命中 仿真评测 ：分类 cs.RO、cs.CV、cs.AI；autonomous driving(journal_ref)

Comments 9 pages, 6 figures, 2 tables

Journal ref NeurIPS 2020 Workshop on Machine Learning for Autonomous Driving (ML4AD)

A Co-Simulation Platform Coupling Land Use, Transportation, and Building Energy: Development and Case Study

耦合土地利用、交通与建筑能源的协同仿真平台：开发与案例研究

Gopindra Sivakumar Nair, Yilin Jiang, Samuel Maurer, James Cook, Nazmul Arefin Khan, Joshua A. Auld, Tianzhen Hong, Arezoo Besharati, Paul Waddell

专题命中 仿真评测 ：occupancy(abstract)

AI总结 该研究开发了集成UrbanSim、POLARIS、CityBES的协同仿真平台，以芝加哥大都市区为例验证其可评估交通与定价政策对土地利用、出行和能源的联合影响。

SCALE-Sim EVA: Design Principles for an Extensible, Visualizable, and Adaptable Accelerator Simulation Framework

SCALE-Sim EVA：可扩展、可可视化且可适配的加速器模拟框架的设计原则

Jingtian Dang, Ritik Raj, Tushar Krishna

专题命中 仿真评测 ：occupancy(abstract)

AI总结 SCALE-Sim EVA是一款面向IR感知加速器建模的可扩展、可可视化、可适配的模拟框架，通过张量命令与命令分解机制计算周期时序，可生成轨迹用于分析执行相关指标，解决了固定加速器模拟器难以扩展的问题。

From Annual Throughput to Vessel Schedules: A Stochastic Generator for Transshipment Hub Simulation

从年度吞吐量到船舶班期：一种用于中转枢纽仿真的随机生成器

Qiaohong Li, Haobin Li, Tianhao Chen, Ek Peng Chew

专题命中 仿真评测 ：occupancy(abstract)

AI总结 该研究针对集装箱中转枢纽仿真的现有模型预测失真问题，提出基于公共港口数据校准的Gamma-GDF随机生成器，经两大超级枢纽验证精度良好，为港口仿真提供稳健基础。

FAIR-Compute: A Roadmap for Fair and Efficient Allocation of Federated Digital Research Infrastructure

FAIR-Compute：联邦数字研究基础设施的公平与高效分配路线图

Konstantinos E. Zachariadis, Ahmed Sayed, Dimitris Fotakis, Angeliki Mathioudaki, Wan Shuen Siaw

专题命中 仿真评测 ：occupancy(abstract)

AI总结 FAIR-Compute 针对联邦数字研究基础设施的分配问题，结合多领域方法与实证研究，发现资源分配存在占用与利用率偏差、调度可优化、联邦需管控等关键问题，提出相关路线图方向。

Comments Final Report to the National Federated Compute Services (NFCS) Flexible Fund

Evaluating Fuzz Testing for Reinforcement Learning Agents

评估强化学习智能体的模糊测试

Zhibin Kang, Hanmo You, Dong Wang, Haiming Zheng, Junjie Chen

机构 * College of Intelligence and Computing, Tianjin University（天津大学智能与计算学部） 纠错

专题命中 仿真评测 ：autonomous driving(abstract)

AI总结 研究针对强化学习智能体模糊测试评估差异问题，通过在三种环境下统一配置对五种方法及随机测试进行基准测试，从多角度评估，揭示不同方法特点，表明模糊测试能提升智能体鲁棒性等，还给出可操作指导。

Transfer Learning Architectures for Scalable Multi-Fidelity Bayesian Optimization

用于可扩展多保真贝叶斯优化的迁移学习架构

Jaewook Lee, Ethan Errington, Christian D. Lorenz, Miao Guo

机构 * King’s College London（伦敦国王学院） 纠错

专题命中 仿真评测 ：self-driving(abstract)

AI总结 研究针对可扩展多保真贝叶斯优化，在相同条件下对11种迁移学习代理和4种GP方法进行基准测试，发现迁移学习代理在分子和材料问题上表现更佳，贪婪利用迁移学习均值是更稳健选择，是分子和材料MFBO的首选代理。

MC-BRIDGE: A Modular Receiver-Chain Simulation Framework for OECT-Based Molecular Communication

MC-BRIDGE：用于基于有机电化学晶体管的分子通信的模块化接收链仿真框架

Hongbin Ni, Ozgur B. Akan

专题命中 仿真评测 ：occupancy(abstract)

AI总结 研究基于OECT的分子通信，提出MC-BRIDGE模块化框架，连接多种过程到电荷域检测，能生成噪声、支持多种键控，通过公共接口估计相关指标并分析干扰，经测试得出满足SER目标的预算上限，揭示多种因素对接收器结论的影响。

Comments 13 pages, 7 figures, submitted to IEEE Transactions on Molecular, Biological, and Multi-Scale Communications (TMBMC)

HybridQC: Hardware-Grounded Simulation of Tightly Integrated Hybrid Quantum-Classical Systems

HybridQC：紧密集成的混合量子-经典系统的硬件基础模拟

Panayiotis Christou, Shuwen Kan, Ying Mao

专题命中 仿真评测 ：occupancy(abstract)

AI总结 研究混合量子-经典系统性能受经典控制等因素限制的问题，提出HybridQC模拟器，通过将HCU建模为可配置图、分解作业并校准测量，可评估混合架构多方面限制，为其性能评估提供系统框架。