自动驾驶

Multimodal Fusion Strategies for Mapping Biophysical Landscape Features

Lucia Gordon, Nico Lang, Catherine Ressijac, Andrew Davies

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、cs.AI

Comments 9 pages, 4 figures, ECCV 2024 Workshop in CV for Ecology

Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping

Shubhra Aich, Wenshan Wang, Parv Maheshwari, Matthew Sivaprakasam, Samuel Triest, Cherie Ho, Jason M. Gregory, John G. Rogers, Sebastian Scherer

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.RO、cs.CV

CaFNet: A Confidence-Driven Framework for Radar Camera Depth Estimation

Huawei Sun, Hao Feng, Julius Ott, Lorenzo Servadei, Robert Wille

专题命中 多传感器融合 ：autonomous driving(abstract)；分类 cs.CV、cs.AI

Comments Accepted by IROS 2024

RaNDT SLAM: Radar SLAM Based on Intensity-Augmented Normal Distributions Transform

Maximilian Hilger, Nils Mandischer, Burkhard Corves

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.RO、cs.CV

Comments This work was accepted by the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

SSRFlow: Semantic-aware Fusion with Spatial Temporal Re-embedding for Real-world Scene Flow

Zhiyang Lu, Qinghan Chen, Zhimin Yuan, Ming Cheng

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、cs.AI

Comments 19 pages,12 figures. arXiv admin note: substantial text overlap with arXiv:2403.07032

RT-Pose: A 4D Radar Tensor-based 3D Human Pose Estimation and Localization Benchmark

Yuan-Hao Ho, Jen-Hao Cheng, Sheng Yao Kuan, Zhongyu Jiang, Wenhao Chai, Hsiang-Wei Huang, Chih-Lung Lin, Jenq-Neng Hwang

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、cs.AI

Comments ECCV 2024

Sparse Beats Dense: Rethinking Supervision in Radar-Camera Depth Completion

Huadong Li, Minhao Jing, Jiajun Liang, Haoqiang Fan, Renhe Ji

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、cs.AI

Comments Accepted to ECCV 2024

Bosch Street Dataset: A Multi-Modal Dataset with Imaging Radar for Automated Driving

Karim Armanious, Maurice Quach, Michael Ulrich, Timo Winterling, Johannes Friesen, Sascha Braun, Daniel Jenet, Yuri Feldman, Eitan Kosman, Philipp Rapp, Volker Fischer, Marc Sons, Lukas Kohns, Daniel Eckstein, Daniela Egbert, Simone Letsch, Corinna Voege, Felix Huttner, Alexander Bartler, Robert Maiwald, Yancong Lin, Ulf Rüegg, Claudius Gläser, Bastian Bischoff, Jascha Freess, Karsten Haug, Kathrin Klee, Holger Caesar

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、cs.AI

MM-Gaussian: 3D Gaussian-based Multi-modal Fusion for Localization and Reconstruction in Unbounded Scenes

Chenyang Wu, Yifan Duan, Xinran Zhang, Yu Sheng, Jianmin Ji, Yanyong Zhang

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.RO、cs.CV

Comments 7 pages, 5 figures

SOAC: Spatio-Temporal Overlap-Aware Multi-Sensor Calibration using Neural Radiance Fields

Quentin Herau, Nathan Piasco, Moussab Bennehar, Luis Roldão, Dzmitry Tsishkou, Cyrille Migniot, Pascal Vasseur, Cédric Demonceaux

专题命中 多传感器融合 ：autonomous driving(abstract)；分类 cs.RO、cs.CV

Comments Accepted at CVPR 2024. Project page: https://qherau.github.io/SOAC/

Towards Dense and Accurate Radar Perception Via Efficient Cross-Modal Diffusion Model

Ruibin Zhang, Donglai Xue, Yuhan Wang, Ruixu Geng, Fei Gao

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.RO、cs.CV

Comments 8 pages, 6 figures, submitted to RA-L

Explicit Interaction for Fusion-Based Place Recognition

Jingyi Xu, Junyi Ma, Qi Wu, Zijie Zhou, Yue Wang, Xieyuanli Chen, Ling Pei

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.RO、cs.CV

Online Targetless Radar-Camera Extrinsic Calibration Based on the Common Features of Radar and Camera

Lei Cheng, Siyang Cao

专题命中 多传感器融合 ：autonomous driving(abstract)；分类 cs.RO、eess.IV

Deep Neighbor Layer Aggregation for Lightweight Self-Supervised Monocular Depth Estimation

Wang Boya, Wang Shuo, Ye Dong, Dou Ziwen

专题命中 多传感器融合 ：autonomous driving(abstract)；分类 cs.CV、cs.AI

Radar Fields: An Extension of Radiance Fields to SAR

Thibaud Ehret, Roger Marí, Dawa Derksen, Nicolas Gasnier, Gabriele Facciolo

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、eess.IV

ADCNet: Learning from Raw Radar Data via Distillation

Bo Yang, Ishan Khatri, Michael Happold, Chulong Chen

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、cs.AI

Comments Update 12/13/2023: upgrade organization and presentation of the paper, adding appendix

Receive, Reason, and React: Drive as You Say with Large Language Models in Autonomous Vehicles

Can Cui, Yunsheng Ma, Xu Cao, Wenqian Ye, Ziran Wang

专题命中 多传感器融合 ：autonomous driving(abstract)；分类 cs.RO、cs.AI

Comments arXiv admin note: text overlap with arXiv:2309.10228

HeightFormer: A Multilevel Interaction and Image-adaptive Classification-regression Network for Monocular Height Estimation with Aerial Images

Zhan Chen, Yidan Zhang, Xiyu Qi, Yongqiang Mao, Xin Zhou, Lulu Niu, Hui Wu, Lei Wang, Yunping Ge

专题命中 多传感器融合 ：autonomous driving(abstract)；分类 cs.CV、cs.AI

DREAM-PCD: Deep Reconstruction and Enhancement of mmWave Radar Pointcloud

Ruixu Geng, Yadong Li, Dongheng Zhang, Jincheng Wu, Yating Gao, Yang Hu, Yan Chen

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.RO、eess.IV

Comments 13 pages, 9 figures

NTU4DRadLM: 4D Radar-centric Multi-Modal Dataset for Localization and Mapping

Jun Zhang, Huayang Zhuge, Yiyao Liu, Guohao Peng, Zhenyu Wu, Haoyuan Zhang, Qiyang Lyu, Heshan Li, Chunyang Zhao, Dogan Kircali, Sanat Mharolkar, Xun Yang, Su Yi, Yuanzhe Wang, Danwei Wang

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.RO、cs.CV

Comments 2023 IEEE International Intelligent Transportation Systems Conference (ITSC 2023)

SelfOdom: Self-supervised Egomotion and Depth Learning via Bi-directional Coarse-to-Fine Scale Recovery

Hao Qu, Lilian Zhang, Xiaoping Hu, Xiaofeng He, Xianfei Pan, Changhao Chen

专题命中 多传感器融合 ：autonomous driving(abstract)；分类 cs.RO、cs.CV

Comments 14 pages, 8 figures, in submission

4DRVO-Net: Deep 4D Radar-Visual Odometry Using Multi-Modal and Multi-Scale Adaptive Fusion

Guirong Zhuo, Shouyi Lu, Huanyu Zhou, Lianqing Zheng, Lu Xiong

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、cs.AI

Comments 14 pages,12 figures

NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric Mapping

Stefan Lionar, Lukas Schmid, Cesar Cadena, Roland Siegwart, Andrei Cramariuc

专题命中 多传感器融合 ：occupancy(abstract)；分类 cs.RO、cs.CV

Comments 3DV 2021. Equal contribution between the first two authors. Code: https://github.com/ethz-asl/neuralblox

Journal ref International Conference on 3D Vision (3DV), 2021, pp. 1279-1289

Multimodal Fusion Transformer for Remote Sensing Image Classification

Swalpa Kumar Roy, Ankur Deria, Danfeng Hong, Behnood Rasti, Antonio Plaza, Jocelyn Chanussot

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、eess.IV

Comments Published in IEEE Transactions on Geoscience and Remote Sensing

A Multi-modal Approach to Single-modal Visual Place Classification

Tomoya Iwasaki, Kanji Tanaka, Kenta Tsukahara

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.RO、cs.CV

Comments 7 pages, 6 figures, 1 table

Multimodal Hyperspectral Image Classification via Interconnected Fusion

Lu Huo, Jiahao Xia, Leijie Zhang, Haimin Zhang, Min Xu

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、cs.AI

Comments 11 pages, five figures

How Much Depth Information can Radar Contribute to a Depth Estimation Model?

Chen-Chou Lo, Patrick Vandewalle

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、eess.IV

Comments published on EI2023, 7 pages, 4 figures, 2 tables

RCDPT: Radar-Camera fusion Dense Prediction Transformer

Chen-Chou Lo, Patrick Vandewalle

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV、eess.IV

Comments 5 pages, 2 figures and 1 table, accepted to ICASSP2023

Real-Time Multi-Modal Semantic Fusion on Unmanned Aerial Vehicles with Label Propagation for Cross-Domain Adaptation

Simon Bultmann, Jan Quenzel, Sven Behnke

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.RO、cs.CV

Comments 35 pages, 18 figures, Accepted for Robotics and Autonomous Systems, Elsevier. arXiv admin note: substantial text overlap with arXiv:2108.06608

RadSegNet: A Reliable Approach to Radar Camera Fusion

Kshitiz Bansal, Keshav Rungta, Dinesh Bharadia

专题命中 多传感器融合 ：autonomous driving(abstract)；分类 cs.CV、cs.AI