自动驾驶

Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review

Yining Shi, Kun Jiang, Jiusi Li, Zelin Qian, Junze Wen, Mengmeng Yang, Ke Wang, Diange Yang

专题命中 感知 ：autonomous driving(title,abstract)；BEV(abstract)；occupancy(abstract)；分类 cs.RO、cs.CV

Multi-Space Alignments Towards Universal LiDAR Segmentation

Youquan Liu, Lingdong Kong, Xiaoyang Wu, Runnan Chen, Xin Li, Liang Pan, Ziwei Liu, Yuexin Ma

专题命中 感知 ：LiDAR(title,abstract)；autonomous driving(abstract)；driving perception(abstract)；分类 cs.RO、cs.CV

Comments CVPR 2024; 33 pages, 14 figures, 14 tables; Code at https://github.com/youquanl/M3Net

UniScene: Multi-Camera Unified Pre-training via 3D Scene Reconstruction for Autonomous Driving

Chen Min, Liang Xiao, Dawei Zhao, Yiming Nie, Bin Dai

专题命中 感知 ：autonomous driving(title,abstract)；LiDAR(abstract)；occupancy(abstract)；分类 cs.RO、cs.CV

Comments Accepted by RAL2024

LabelFormer: Object Trajectory Refinement for Offboard Perception from LiDAR Point Clouds

Anqi Joyce Yang, Sergio Casas, Nikita Dvornik, Sean Segal, Yuwen Xiong, Jordan Sir Kwang Hu, Carter Fang, Raquel Urtasun

专题命中 感知 ：LiDAR(title,abstract)；self-driving(abstract)；driving perception(abstract)；分类 cs.RO、cs.CV

Comments 20 pages, 8 figures, 7 tables

Journal ref CoRL 2023

Multi-camera Bird's Eye View Perception for Autonomous Driving

David Unger, Nikhil Gosala, Varun Ravi Kumar, Shubhankar Borse, Abhinav Valada, Senthil Yogamani

专题命中 感知 ：autonomous driving(title,abstract)；BEV(abstract)；LiDAR(abstract)；分类 cs.RO、cs.CV

Comments Taylor & Francis (CRC Press) book chapter. Book title: Computer Vision: Challenges, Trends, and Opportunities

NVRadarNet: Real-Time Radar Obstacle and Free Space Detection for Autonomous Driving

Alexander Popov, Patrik Gebhardt, Ke Chen, Ryan Oldja, Heeseok Lee, Shane Murray, Ruchi Bhargava, Nikolai Smolyanskiy

专题命中 感知 ：autonomous driving(title,abstract)；self-driving(abstract)；BEV(abstract)；分类 cs.RO、cs.CV

Comments 7 pages, 6 figures, ICRA 2023 conference, for associated video file, see https://youtu.be/WlwJJMltoJY

Enabling 3D Object Detection with a Low-Resolution LiDAR

Lin Bai, Yiming Zhao, Xinming Huang

专题命中 感知 ：LiDAR(title,abstract)；autonomous driving(abstract)；BEV(abstract)；分类 cs.RO、cs.CV

LiMoSeg: Real-time Bird's Eye View based LiDAR Motion Segmentation

Sambit Mohapatra, Mona Hodaei, Senthil Yogamani, Stefan Milz, Heinrich Gotzig, Martin Simon, Hazem Rashed, Patrick Maeder

专题命中 感知 ：LiDAR(title,abstract)；autonomous driving(abstract)；BEV(abstract)；分类 cs.RO、cs.CV

Comments Accepted for Presentation at International Conference on Computer Vision Theory and Applications (VISAPP 2022)

MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding

Kunyu Peng, Juncong Fei, Kailun Yang, Alina Roitberg, Jiaming Zhang, Frank Bieder, Philipp Heidenreich, Christoph Stiller, Rainer Stiefelhagen

专题命中 感知 ：LiDAR(title,abstract)；self-driving(abstract)；occupancy(abstract)；分类 cs.RO、cs.CV

Comments Accepted to IEEE Transactions on Intelligent Transportation Systems (T-ITS). Code is publicly available at https://github.com/KPeng9510/MASS

MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views

Ke Chen, Ryan Oldja, Nikolai Smolyanskiy, Stan Birchfield, Alexander Popov, David Wehr, Ibrahim Eden, Joachim Pehserl

专题命中 感知 ：autonomous driving(title,abstract)；self-driving(abstract)；LiDAR(abstract)；分类 cs.RO、cs.CV

Comments IROS 2020 conference (submitted March 1st, 2020). For accompanying video, see https://youtu.be/2ck5_sToayc

Physically Realizable Adversarial Examples for LiDAR Object Detection

James Tu, Mengye Ren, Siva Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun

专题命中 感知 ：LiDAR(title,abstract)；autonomous driving(abstract)；self-driving(abstract)；分类 cs.RO、cs.CV

Comments Accepted to CVPR 2020

From perception to control: an autonomous driving system for a formula student driverless car

Tairan Chen, Zirui Li, Yiting He, Zewen Xu, Zhe Yan, Huiqian Li

专题命中 感知 ：autonomous driving(title)；self-driving(abstract)；LiDAR(abstract)；occupancy(abstract)

Brain Inspired Cognitive Model with Attention for Self-Driving Cars

Shitao Chen, Songyi Zhang, Jinghao Shang, Badong Chen, Nanning Zheng

专题命中 感知 ：self-driving(title,abstract)；autonomous driving(abstract)；end-to-end driving(abstract)；分类 cs.RO、cs.CV

Comments 13 pages, 10 figures

Towards a Systematic Risk Assessment of Deep Neural Network Limitations in Autonomous Driving Perception

面向自动驾驶感知中深度神经网络局限性的系统性风险评估

Svetlana Pavlitska, Christopher Gerking, J. Marius Zöllner

机构 * FZI Research Center for Information Technology, Germany（德国弗劳恩霍夫信息技术研究所） ； Karlsruhe Institute of Technology, Germany（德国卡尔斯鲁厄理工学院） 纠错

专题命中 感知 ：autonomous driving(title,abstract)；driving perception(title)

AI总结 本文提出结合ISO 26262和ISO/SAE 21434标准的风险评估流程，系统分析深度神经网络在自动驾驶感知中的固有局限性带来的风险。

Comments Accepted for publication at the SECAI workshop at ESORICS 2025

Geometry-Grounded Unified 3D Perception for Autonomous Driving

面向自动驾驶的基于几何的统一3D感知

Longfei Xu, Xiaohui Wang, Zehao Huang, Han Li, Ya Yang, Naiyan Wang, Si Liu

专题命中 感知 ：autonomous driving(title,abstract)；occupancy(abstract)；driving perception(abstract)；分类 cs.CV

AI总结 该研究针对现有自动驾驶3D感知框架无法保留显式度量几何的问题，提出GeoUP框架，通过分解跨图像交互并注入射线图编码实现统一3D感知，在多数据集上达到SOTA性能。

Talk2Sensors: 3D Visual Grounding in Autonomous Driving via Sensor-Adaptive Physical Cue Matching

Talk2Sensors：基于传感器自适应物理线索匹配的自动驾驶3D视觉 grounding

Runwei Guan, Di Tian, Ningwei Ouyang, Ruixiao Zhang, Shaofeng Liang, Haocheng Zhao, Lianqing Zheng, Xiaokai Bai, Guotao Wang, Daizong Liu, Henghui Ding, Hui Xiong

机构 * Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）人工智能学域） ； MMLab, CUHK（香港中文大学MMLab） ； School of Transportation Science and Engineering, Harbin Institute of Technology（哈尔滨工业大学交通科学与工程学院） ； School of Advanced Technology, Xi’an Jiaotong-Liverpool University（西交利物浦大学先进技术学院） ； School of Electronics and Computer Science, University of Southampton（南安普顿大学电子与计算机科学学院） ； School of Intelligent Manufacturing and Smart Transportation, Suzhou City University（苏州城市学院智能制造与智能交通学院） ； Qingdao University of Science and Technology（青岛科技大学） ； Institute for Math & AI, Wuhan University（武汉大学数学与人工智能研究院） ； Institute of Big Data, Fudan University（复旦大学大数据研究院） 纠错

专题命中 感知 ：autonomous driving(title,abstract)；LiDAR(abstract,abstract_cn)；分类 cs.CV

AI总结 针对现有室外3D视觉 grounding 未充分利用多传感器互补物理属性的问题，提出首个多传感器数据集Talk2Sensors及TSFormer框架，在相关基准上实现了最优性能。

Comments 14 pages, 12 figures

ViCo3D: Empowering LiDAR-based Collaborative 3D Object Detection with Vision Foundation Models

ViCo3D：利用视觉基础模型增强基于激光雷达的协作式3D目标检测

Haojie Ren, Songrui Luo, Lingfeng Wang, Yan Xia, Yao Li, Jing Li, Lu Zhang, Jiajun Deng, Yanyong Zhang

机构 * University of Science and Technology of China（中国科学技术大学） 纠错

专题命中 感知 ：LiDAR(title,abstract)；BEV(abstract,abstract_cn)；分类 cs.CV

AI总结 研究针对V2X系统中基于激光雷达协作式3D感知的不足，提出ViCo3D框架。通过将点云投影为图像让VFM提取特征，引入融合模块及跨智能体融合策略，实现了先进的3D检测性能，提升了协作增益。

ATLAS: A Large-Scale Evaluation Benchmark for Adversarial LiDAR Perception

ATLAS：面向对抗性激光雷达感知的大规模评估基准

Mellon M. Zhang, Siddhant Panse, Zimo Fan, Akshal Dhal, Rishit Sarkar, Glen Chou

专题命中 感知 ：LiDAR(title,abstract)；autonomous driving(abstract)；driving perception(abstract)；分类 cs.CV

AI总结 针对黑盒传感器攻击下激光雷达感知模型的鲁棒性评估空白，提出首个大规模物理驱动基准ATLAS，通过点注入和点移除两种攻击模式，揭示模型性能与鲁棒性的非对称性，并溯源至标准数据增强方法。

Comments preprint

PanDA: Unsupervised Domain Adaptation for Multimodal 3D Panoptic Segmentation in Autonomous Driving

PanDA: 无监督领域自适应用于自动驾驶中的多模态3D全景分割

Yining Pan, Shijie Li, Yuchen Wu, Xulei Yang, Na Zhao

机构 * Singapore University of Technology and Design（新加坡科技设计大学） ； Institute for Infocomm Research (I2R), A*STAR, Singapore（新加坡资讯通信研究院（I2R），A*STAR，新加坡） 纠错

专题命中 感知 ：autonomous driving(title,abstract)；LiDAR(abstract,abstract_cn)；分类 cs.CV

AI总结 本文提出PanDA框架，针对多模态3D全景分割的无监督领域自适应问题，通过不对称多模态增强和双专家伪标签细化模块提升鲁棒性和伪标签完整性，实验表明在多种领域转移场景下超越现有SOTA方法。

Comments Accepted at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2026

AurigaNet: A Real-Time Multi-Task Network for Enhanced Urban Driving Perception

AurigaNet: 一种用于增强城市驾驶感知的实时多任务网络

Kiarash Ghasemzadeh, Sedigheh Dehghani

机构 * University of Alberta（阿尔伯塔大学） ； Shahid Beheshti University（沙希德·贝赫什提大学） 纠错

专题命中 感知 ：driving perception(title,abstract)；autonomous driving(abstract)；self-driving(abstract)；分类 cs.CV

AI总结 AurigaNet通过端到端实例分割提升自动驾驶感知性能，实现高精度的可驾驶区域分割、车道检测和目标识别。

OmniHD-Scenes: A Next-Generation Multimodal Dataset for Autonomous Driving

OmniHD-Scenes：面向自动驾驶的下一代多模态数据集

Lianqing Zheng, Long Yang, Qunshu Lin, Wenjin Ai, Minghao Liu, Shouyi Lu, Jianan Liu, Hongze Ren, Jingyue Mo, Xiaokai Bai, Jie Bai, Zhixiong Ma, Xichan Zhu

机构 * School of Automotive Studies, Tongji University（同济大学汽车学院） ； College of Computer Science and Technology, Zhejiang University（浙江大学计算机科学与技术学院） ； AI Foundation（2077AI基金会） ； Momoni AI ； College of Information Science and Electronic Engineering, Zhejiang University（浙江大学信息科学与电子工程学院） ； School of Information and Electrical Engineering, Hangzhou City University（杭州城市学院信息与电气工程学院） 纠错

专题命中 感知 ：autonomous driving(title,abstract)；LiDAR(abstract)；occupancy(abstract)；分类 cs.CV

AI总结 OmniHD-Scenes提出了一种大规模多模态数据集，结合多种传感器数据，用于提升自动驾驶的3D检测和语义预测性能。

Comments Accepted by IEEE TPAMI

Spatial Retrieval Augmented Autonomous Driving

空间检索增强的自动驾驶

Xiaosong Jia, Chenhe Zhang, Yule Jiang, Songbur Wong, Zhiyuan Zhang, Chen Chen, Shaofeng Zhang, Xuanhe Zhou, Xue Yang, Junchi Yan, Yu-Gang Jiang

机构 * Institute of Trustworthy Embodied AI, Fudan University（可信具身人工智能研究院，复旦大学） ； Shanghai Jiao Tong University（上海交通大学） ； Key Laboratory of Target Cognition and Application Technology, Aerospace Information Research Institute, Chinese Academy of Sciences（目标认知与应用技术重点实验室，航天信息研究所，中国科学院） ； University of Science and Technology of China（中国科学技术大学） 纠错

专题命中 感知 ：autonomous driving(title,abstract)；LiDAR(abstract)；occupancy(abstract)；分类 cs.CV

AI总结 本文提出空间检索范式，通过引入离线地理图像提升自动驾驶任务性能，扩展nuScenes数据集并建立多个基准测试。

Comments Demo Page: https://spatialretrievalad.github.io/ with open sourced code, dataset, and checkpoints

HENet++: Hybrid Encoding and Multi-task Learning for 3D Perception and End-to-end Autonomous Driving

Zhongyu Xia, Zhiwei Lin, Yongtao Wang, Ming-Hsuan Yang

机构 * University of California, Merced（加州大学默塞德分校） 纠错

专题命中 感知 ：autonomous driving(title,abstract)；BEV(abstract)；occupancy(abstract)；分类 cs.CV

Comments Preliminary version, 19 pages

Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving

Shumin Wang, Zhuoran Yang, Lidian Wang, Zhipeng Tang, Heng Li, Lehan Pan, Sha Zhang, Jie Peng, Jianmin Ji, Yanyong Zhang

专题命中 感知 ：autonomous driving(title,abstract)；BEV(abstract)；occupancy(abstract)；分类 cs.CV

POD: Predictive Object Detection with Single-Frame FMCW LiDAR Point Cloud

Yining Shi, Kun Jiang, Xin Zhao, Kangan Qian, Chuchu Xie, Tuopu Wen, Mengmeng Yang, Diange Yang

专题命中 感知 ：LiDAR(title,abstract)；autonomous driving(abstract)；BEV(abstract)；分类 cs.CV

MutualForce: Mutual-Aware Enhancement for 4D Radar-LiDAR 3D Object Detection

Xiangyuan Peng, Huawei Sun, Kay Bierzynski, Anton Fischbacher, Lorenzo Servadei, Robert Wille

专题命中 感知 ：LiDAR(title,abstract)；autonomous driving(abstract)；BEV(abstract)；分类 cs.CV

Comments Accepted by ICASSP 2025

GraphBEV: Towards Robust BEV Feature Alignment for Multi-Modal 3D Object Detection

Ziying Song, Lei Yang, Shaoqing Xu, Lin Liu, Dongyang Xu, Caiyan Jia, Feiyang Jia, Li Wang

专题命中 感知 ：BEV(title,abstract)；autonomous driving(abstract)；LiDAR(abstract)；分类 cs.CV

Reliability-Driven LiDAR-Camera Fusion for Robust 3D Object Detection

Reza Sadeghian, Niloofar Hooshyaripour, Chris Joslin, WonSook Lee

专题命中 感知 ：LiDAR(title,abstract)；autonomous driving(abstract)；BEV(abstract)；分类 cs.CV

A Novel Vision Transformer for Camera-LiDAR Fusion based Traffic Object Segmentation

Toomas Tahves, Junyi Gu, Mauro Bellone, Raivo Sell

专题命中 感知 ：LiDAR(title,abstract)；autonomous driving(abstract)；driving perception(abstract)；分类 cs.CV

Comments International Conference on Agents and Artificial Intelligence 2025

TiGDistill-BEV: Multi-view BEV 3D Object Detection via Target Inner-Geometry Learning Distillation

Shaoqing Xu, Fang Li, Peixiang Huang, Ziying Song, Zhi-Xin Yang

专题命中 感知 ：BEV(title,abstract)；autonomous driving(abstract)；LiDAR(abstract)；分类 cs.CV

Comments 13 pages, 8 figures. arXiv admin note: substantial text overlap with arXiv:2212.13979