自动驾驶

BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

Zhiqi Li, Wenhai Wang, Hongyang Li, Enze Xie, Chonghao Sima, Tong Lu, Qiao Yu, Jifeng Dai

专题命中 BEV与占用 ：autonomous driving(abstract)；BEV(abstract)；LiDAR(abstract)；driving perception(abstract)

Comments Accepted to ECCV 2022

RoadWeaver: Large-Scale Lane-Level HD Map Generation from Scratch for Autonomous Driving Simulation

RoadWeaver：面向自动驾驶仿真的从零开始大规模车道级高清地图生成

Yueyuan Li, Zexi Chen, Weijie Xi, Mingyang Jiang, Songan Zhang, Hanyang Zhuang, Ming Yang

专题命中 BEV与占用 ：autonomous driving(title,abstract)；分类 cs.RO、cs.AI

AI总结 该研究提出RoadWeaver框架，以由粗到细的方式从零生成大规模车道级高清地图，其性能优于现有最优方法，生成的地图可直接用于自动驾驶仿真。

Comments 8 pages, 6 figures, 2 tables

GEM-Occ: From Visual Geometry Evidence to Embodied Semantic Occupancy Memory

GEM-Occ：从视觉几何证据到具身语义占用记忆

Hu Zhu, Bohan Li, Xianda Guo, Hongsi Liu, Baorui Peng, Mingqi Yuan, Xin Jin, Wenjun Zeng, Chang Wen Chen

机构 * The Hong Kong Polytechnic University（香港理工大学） ； Eastern Institute of Technology（东部理工学院） ； Shanghai Jiao Tong University（上海交通大学） ； Wuhan University（武汉大学） ； The University of Hong Kong（香港大学） ； Georgia Institute of Technology（佐治亚理工学院） 纠错

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.CV

AI总结 研究针对现有室内占用基准和方法对长距离语义映射探索不足的问题，提出GEM-Occ框架，将局部视觉几何预测转化为语义高斯占用证据等并融合到持久分层记忆中，实验证明该框架在多方面优于现有基线。

Comments 19 pages, 6 figures. Project page: https://zhuhu00.top/GEM-Occ/

FLM-Occ: Feed-forward Likelihood Maximization for Efficient Indoor Occupancy Prediction

FLM-Occ: 前向似然最大化用于高效室内占据预测

Guangcheng Chen, Lihuang Fang, Huaqi Tao, Yicheng He, Li He, Hong Zhang

机构 * Southern University of Science and Technology（南方科技大学） ； Guangdong Laboratory of Artificial Intelligence and Digital Economy (Shenzhen)（广东省人工智能与数字经济实验室（深圳）） ； Shenzhen Key Laboratory of Robotics and Computer Vision（深圳市机器人视觉与感知重点实验室） 纠错

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.CV

AI总结 针对现有方法在空区域产生虚假基元的问题，提出前向似然最大化框架，将占据预测建模为体素分布估计，通过最大化真实占据体素的似然来训练网络，实现高效准确的室内占据预测。

Comments Accepted to ECCV 2026

FreeOcc: Training-Free Embodied Open-Vocabulary Occupancy Prediction

FreeOcc: 无需训练的具身开放词汇占用预测

Zeyu Jiang, Changqing Zhou, Xingxing Zuo, Changhao Chen

机构 * The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州）） ； MBZUAI 纠错

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.CV

AI总结 FreeOcc通过四层流程实现无需3D标注的开放词汇占用预测，相比传统方法在EmbodiedOcc-ScanNet上提升IoU和mIoU超过2倍，并引入ReplicaOcc基准测试新环境性能。

Comments RSS 2026

Persistent Autoregressive Mapping with Traffic Rules for Autonomous Driving

具有交通规则的持久自回归映射用于自动驾驶

Shiyi Liang, Xinyuan Chang, Changjie Wu, Huiyuan Yan, Yifan Bai, Xinran Liu, Hang Zhang, Yujian Yuan, Shuang Zeng, Mu Xu, Xing Wei

专题命中 BEV与占用 ：autonomous driving(title,abstract)；分类 cs.RO、cs.AI

AI总结 本文提出PAMR框架，通过视觉观测进行车道向量与交通规则的自回归联合构建，解决交通规则在长时间驾驶序列中的持续有效性问题。

Comments AAAI2026

BEV-Patch-PF: Particle Filtering with BEV-Aerial Feature Matching for Off-Road Geo-Localization

BEV-Patch-PF：基于鸟瞰图空域特征匹配的无GPS轨迹定位系统

Dongmyeong Lee, Jesse Quattrociocchi, Christian Ellis, Rwik Rana, Amanda Adkins, Adam Uccello, Garrett Warnell, Joydeep Biswas

机构 * University of Texas at Austin（德克萨斯大学奥斯汀分校） ； DEVCOM Army Research Laboratory（国防部陆军研究实验室） 纠错

专题命中 BEV与占用 ：BEV(title,abstract)；分类 cs.RO、cs.CV

AI总结 BEV-Patch-PF通过结合鸟瞰图与空域特征匹配，实现了无GPS的非公路地理定位，显著降低轨迹误差并实现实时运行。

SPOT-Occ: Sparse Prototype-guided Transformer for Camera-based 3D Occupancy Prediction

SPOT-Occ: 基于稀疏原型的Transformer用于基于相机的3D占用预测

Suzeyu Chen, Leheng Li, Ying-Cong Chen

机构 * Artificial Intelligence Thrust, The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学人工智能方向（广州）） ； Department of Computer Science and Engineering, The Hong Kong University of Science and Technology（香港科学与技术大学计算机科学与工程系） 纠错

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.CV

AI总结 SPOT-Occ提出了一种基于稀疏原型的Transformer解码器，通过引导特征选择和聚焦聚合提升基于相机的3D占用预测的效率与精度。

Comments 8 pages, 6 figures

Robust Robotic Exploration and Mapping Using Generative Occupancy Map Synthesis

使用生成占用地图合成的鲁棒机器人探索与建图

Lorin Achey, Alec Reed, Brendan Crowe, Bradley Hayes, Christoffer Heckman

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.AI

AI总结 本文提出了一种基于生成占用地图合成的鲁棒机器人探索方法，通过实时融合预测提升地图质量和可通行性，实验表明其在不同环境中提升了探索一致性。

Comments arXiv admin note: text overlap with arXiv:2409.10681

Journal ref Auton Robot 50, 8 (2026)

DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes

DynamicCity: 从动态场景生成大规模4D占用图

Hengwei Bian, Lingdong Kong, Haozhe Xie, Liang Pan, Yu Qiao, Ziwei Liu

机构 * WorldBench Team（WorldBench团队） 纠错

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.CV

AI总结 DynamicCity通过VAE和DiT模型生成高质量动态4D占用图，提升拟合质量与训练效率。

Comments ICLR 2025 Spotlight; 35 pages, 18 figures, 15 tables; Project Page at https://dynamic-city.github.io/

CSMapping: Scalable Crowdsourced Semantic Mapping and Topology Inference for Autonomous Driving

CSMapping: 可扩展的众包语义制图与拓扑推断用于自动驾驶

Zhijian Qiao, Zehuan Yu, Tong Li, Chih-Chung Chou, Wenchao Ding, Shaojie Shen

机构 * the Department of Electronic and Computer Engineering, the Hong Kong University of Science and Technology, Hong Kong, China（电子与计算机工程系，香港科技大学，香港，中国） ； the Academy for Engineering and Technology, Fudan University, Shanghai, China（工程与技术学院，复旦大学，上海，中国） ； Zhuoyu Technology Co., Ltd., Shenzhen, China（珠海优创科技有限公司，深圳，中国） 纠错

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

AI总结 CSMapping通过潜在扩散模型和拓扑优化方法，实现高质量的语义地图和道路中心线生成，适用于自动驾驶场景。

Adversarial Patch Attacks on Vision-Based Cargo Occupancy Estimation via Differentiable 3D Simulation

基于可微3D模拟的视觉货物占用估计中的对抗性补丁攻击

Mohamed Rissal Hedna, Sesugh Samuel Nder

机构 * Department of Informatics University of Hamburg（信息学院海德堡大学） 纠错

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.CV、cs.AI

AI总结 本文首次研究了在物理真实、完全模拟的3D场景中针对货物占用估计的对抗性补丁攻击，通过3D优化补丁在拒绝服务场景中达到84.94%的攻击成功率。

Comments 9 pages, 5 figures, 1 algorithm

Vision-Only Gaussian Splatting for Collaborative Semantic Occupancy Prediction

仅视觉的高斯散射用于协作语义占用预测

Cheng Chen, Hao Huang, Saurabh Bagchi

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.CV

AI总结 本研究提出基于稀疏3D语义高斯散射的协作语义占用预测方法，通过高效融合和减少通信开销，提升了协作感知的性能和鲁棒性。

Comments Accepted by AAAI 2026 (Oral)

Semantic Causality-Aware Vision-Based 3D Occupancy Prediction

Dubing Chen, Huan Zheng, Yucheng Zhou, Xianfei Li, Wenlong Liao, Tao He, Pai Peng, Jianbing Shen

机构 * SKL-IOTSC, CIS, University of Macau（澳门大学SKL-IOTSC研究所、CIS学院） ； COWAROBOT Co. Ltd.（COWAROBOT公司） 纠错

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.CV、cs.AI

Comments ICCV 2025

Beyond BEV: Optimizing Point-Level Tokens for Collaborative Perception

Yang Li, Quan Yuan, Guiyang Luo, Xiaoyuan Fu, Rui Pan, Yujia Yang, Congzhang Shao, Yuewen Liu, Jinglin Li

专题命中 BEV与占用 ：BEV(title,abstract)；分类 cs.CV、cs.AI

EmbodiedOcc: Embodied 3D Occupancy Prediction for Vision-based Online Scene Understanding

Yuqi Wu, Wenzhao Zheng, Sicheng Zuo, Yuanhui Huang, Jie Zhou, Jiwen Lu

机构 * Department of Automation, Tsinghua University（自动化系，清华大学） 纠错

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.CV、cs.AI

Comments Accepted by ICCV2025. Code: https://github.com/YkiWu/EmbodiedOcc

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning

Jiacheng Zuo, Haibo Hu, Zikang Zhou, Yufei Cui, Ziquan Liu, Jianping Wang, Nan Guan, Jin Wang, Chun Jason Xue

机构 * Department of Future Science and Engineering, Soochow University（苏州大学未来科学与工程学院） ； Department of Computer Science, City University of Hong Kong（城市大学计算机科学系） ； Department of Computer Science, McGill University（麦吉尔大学计算机科学系） ； School of Electronic Engineering and Computer Science, Queen Mary University of London（伦敦大学玛丽女王学院电子工程与计算机科学学院） ； Department of Computer Science, Mohamed bin Zayed University of Artificial Intelligence（Mohamed bin Zayed人工智能大学计算机科学系） 纠错

专题命中 BEV与占用 ：autonomous driving(title,abstract)；分类 cs.CV、cs.AI

LUDO: Low-Latency Understanding of Deformable Objects using Point Cloud Occupancy Functions

Pit Henrich, Franziska Mathis-Ullrich, Paul Maria Scheikl

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.CV

Comments Published in IEEE Transactions on Robotics (T-RO)

SEPT: Standard-Definition Map Enhanced Scene Perception and Topology Reasoning for Autonomous Driving

Muleilan Pei, Jiayao Shan, Peiliang Li, Jieqi Shi, Jing Huo, Yang Gao, Shaojie Shen

机构 * Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology（电子与计算机工程系，香港科学与技术大学） ； Zhuoyu Technology（卓予科技） ； State Key Laboratory for Novel Software Technology, Nanjing University（新型软件技术国家重点实验室，南京大学） 纠错

专题命中 BEV与占用 ：autonomous driving(title)；BEV(abstract)；分类 cs.RO、cs.CV

Comments Accepted by IEEE Robotics and Automation Letters

OccCylindrical: Multi-Modal Fusion with Cylindrical Representation for 3D Semantic Occupancy Prediction

Zhenxing Ming, Julie Stephany Berrio, Mao Shan, Yaoqi Huang, Hongyu Lyu, Nguyen Hoang Khoi Tran, Tzu-Yun Tseng, Stewart Worrall

机构 * Australian Centre for Robotics (ACFR) at the University of Sydney（澳大利亚机器人中心（ACFR）于悉尼大学） 纠错

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.CV

SA-Occ: Satellite-Assisted 3D Occupancy Prediction in Real World

Chen Chen, Zhirui Wang, Taowei Sheng, Yi Jiang, Yundu Li, Peirui Cheng, Luning Zhang, Kaiqiang Chen, Yanfeng Hu, Xue Yang, Xian Sun

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.CV、cs.AI

Comments 10 pages

3D Occupancy Prediction with Low-Resolution Queries via Prototype-aware View Transformation

Gyeongrok Oh, Sungjune Kim, Heeju Ko, Hyung-gun Chi, Jinkyu Kim, Dongwook Lee, Daehyun Ji, Sungjoon Choi, Sujin Jang, Sangpil Kim

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.CV、cs.AI

Comments Accepted to CVPR2025

BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation

Jonas Schramm, Niclas Vödisch, Kürsat Petek, B Ravi Kiran, Senthil Yogamani, Wolfram Burgard, Abhinav Valada

专题命中 BEV与占用 ：BEV(title,abstract)；分类 cs.RO、cs.CV

Comments Accepted for the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024

Journal ref IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024, pp. 1435-1442

SOccDPT: Semi-Supervised 3D Semantic Occupancy from Dense Prediction Transformers trained under memory constraints

Aditya Nalgunda Ganesh

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.CV、cs.AI

Comments This work has been submitted to the ICRA 2024 IEEE for possible publication

Journal ref Adv. Artif. Intell. Mach. Learn. 4 (2024) 2201-2212

CVT-Occ: Cost Volume Temporal Fusion for 3D Occupancy Prediction

Zhangchen Ye, Tao Jiang, Chenfeng Xu, Yiming Li, Hang Zhao

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.CV、cs.AI

Comments Accepted to ECCV 2024

OpenOcc: Open Vocabulary 3D Scene Reconstruction via Occupancy Representation

Haochen Jiang, Yueming Xu, Yihan Zeng, Hang Xu, Wei Zhang, Jianfeng Feng, Li Zhang

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.CV

Comments This work is accepted by IROS 2024

Local Occupancy-Enhanced Object Grasping with Multiple Triplanar Projection

Kangqi Ma, Hao Dong, Yadong Mu

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.RO、cs.AI

Revisit Human-Scene Interaction via Space Occupancy

Xinpeng Liu, Haowen Hou, Yanchao Yang, Yong-Lu Li, Cewu Lu

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.CV、cs.AI

Comments To appear in ECCV 2024. The first two authors contributed equally. Yong-Lu Li is the corresponding author. Project page: https://foruck.github.io/occu-page/

Video Occupancy Models

Manan Tomar, Philippe Hansen-Estruch, Philip Bachman, Alex Lamb, John Langford, Matthew E. Taylor, Sergey Levine

专题命中 BEV与占用 ：occupancy(title,abstract)；分类 cs.CV、cs.AI

Accelerating Online Mapping and Behavior Prediction via Direct BEV Feature Attention

Xunjiang Gu, Guanyu Song, Igor Gilitschenski, Marco Pavone, Boris Ivanovic

专题命中 BEV与占用 ：BEV(title,abstract)；分类 cs.RO、cs.CV

Comments 21 pages, 10 figures, 6 tables. ECCV 2024