SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2699184 · Cited by 22,392

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2016) · arXiv · doi:10.48550/arxiv.1606.00915 · Cited by 22,392

YOLOv3: An Incremental Improvement

Redmon, J., & Farhadi, A. (2018) · arXiv · doi:10.48550/arxiv.1804.02767 · Cited by 17,141

Are we ready for autonomous driving? The KITTI vision benchmark suite

Geiger, A., Lenz, P., & Urtasun, R. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248074 · Cited by 14,897

The Cityscapes Dataset for Semantic Urban Scene Understanding

Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., Franke, U., Roth, S., & Schiele, B. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.350 · Cited by 12,433

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric SpacePreprint

Qi, C. R., Yi, L., Su, H., & Guibas, L. J. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.02413 · Cited by 10,099

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Charles, R., Su, H., Mo, K., & Guibas, L. J. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.16 · Cited by 10,029

The Pascal Visual Object Classes Challenge: A Retrospective

Everingham, M., Eslami, S. M. A., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-014-0733-5 · Cited by 7,139

Indoor segmentation and support inference from rgbd images

Silberman, N., Hoiem, D., Kohli, P., & Fergus, R. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33715-4_54 · Cited by 5,760

Vulnerable road user detection and safety enhancement: A comprehensive survey

Silva, R. M., Azevedo, G. F., Berto, M. V. V., Rocha, J. R., Fidelis, E. C., Nogueira, M. V., Lisboa, P., & Almeida, T. A. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128529 · Cited by 30

Robust Self-Supervised LiDAR Odometry Via Representative Structure Discovery and 3D Inherent Error Modeling

Xu, Y., Lin, J., Shi, J., Zhang, G., Wang, X., & Li, H. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3140794 · Cited by 24

Make it Dense: Self-Supervised Geometric Scan Completion of Sparse 3D LiDAR Scans in Large Outdoor Environments

Vizzo, I., Mersch, B., Marcuzzi, R., Wiesmann, L., Behley, J., & Stachniss, C. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3187255 · Cited by 24

Online Semantic-Assisted Topological Map Building With LiDAR in Large-Scale Outdoor Environments: Toward Robust Place Recognition

He, G., Zhang, Q., & Zhuang, Y. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3191648 · Cited by 24

MapCleaner: Efficiently Removing Moving Objects from Point Cloud Maps in Autonomous Driving Scenarios

Fu, H., Xue, H., & Xie, G. (2022) · Remote Sensing · doi:10.3390/rs14184496 · Cited by 24

LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation

Hu, Z., Bai, X., Zhang, R., Wang, X., Sun, G., Fu, H., & Tai, C. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19812-0_15 · Cited by 24

Category-Level Adversaries for Outdoor LiDAR Point Clouds Cross-Domain Semantic Segmentation

Yuan, Z., Wen, C., Cheng, M., Su, Y., Liu, W., Yu, S., & Wang, C. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3219853 · Cited by 24

Learning to Simulate Realistic LiDARs

Guillard, B., Vemprala, S. H., Gupta, J. K., Mikšík, O., Vineet, V., Fua, P., & Kapoor, A. (2022) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros47612.2022.9981120 · Cited by 24

Real-Time LiDAR Point-Cloud Moving Object Segmentation for Autonomous Driving

Xie, X., Wei, H., & Yang, Y. (2023) · Sensors · doi:10.3390/s23010547 · Cited by 24

High Precision Leaf Instance Segmentation for Phenotyping in Point Clouds Obtained Under Real Field Conditions

Marks, E., Sodano, M., Magistri, F., Wiesmann, L., Desai, D., Marcuzzi, R., Behley, J., & Stachniss, C. (2023) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2023.3288383 · Cited by 24

Adversarially Masking Synthetic to Mimic Real: Adaptive Noise Injection for Point Cloud Segmentation Adaptation

Li, G., Kang, G., Wang, X., Wei, Y., & Yang, Y. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.01960 · Cited by 24

Reliability-Adaptive Consistency Regularization for Weakly-Supervised Point Cloud Segmentation

Wu, Z., Wu, Y., Lin, G., & Cai, J. (2024) · International Journal of Computer Vision · doi:10.1007/s11263-023-01975-8 · Cited by 24

Retro-FPN: Retrospective Feature Pyramid Network for Point Cloud Semantic Segmentation

Xiang, P., Wen, X., Liu, Y.-S., Zhang, H., Fang, Y., & Han, Z. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01634 · Cited by 24

Enhancing Context Models for Point Cloud Geometry Compression With Context Feature Residuals and Multi-Loss

Sun, C., Yuan, H., Li, S., Lu, X., & Hamzaoui, R. (2024) · IEEE Journal on Emerging and Selected Topics in Circuits and Systems · doi:10.1109/jetcas.2024.3367729 · Cited by 24

A robust data-model dual-driven fusion with uncertainty estimation for LiDAR–IMU localization system

Li, Q., Zhuang, Y., Huai, J., Wang, X., Wang, B., & Cao, Y. (2024) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2024.03.008 · Cited by 24

基于深度学习的三维点云处理方法研究进展

Yiquan, 吴. W., Huixian, 陈. C., & Yao, 张. Z. (2024) · Chinese Journal of Lasers · doi:10.3788/cjl230924 · Cited by 24

Ground segmentation based point cloud feature extraction for 3D LiDAR SLAM enhancement

Tsai, T.-C., & Peng, C.-C. (2024) · Measurement · doi:10.1016/j.measurement.2024.114890 · Cited by 24

SALUDA: Surface-based Automotive Lidar Unsupervised Domain Adaptation

Michele, B., Boulch, A., Puy, G., Vu, T.-H., Marlet, R., & Courty, N. (2024) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv62453.2024.00134 · Cited by 24

S4C: Self-Supervised Semantic Scene Completion With Neural Fields

Hayler, A., Wimbauer, F., Muhle, D., Rupprecht, C., & Cremers, D. (2024) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv62453.2024.00133 · Cited by 31

Deep Learning-Based Vision Systems for Robot Semantic Navigation: An Experimental Study

Alotaibi, A. T., Alatawi, H. A., Binnouh, A., Duwayriat, L., Alhmiedat, T. A., & Alia, O. M. (2024) · Technologies · doi:10.3390/technologies12090157 · Cited by 24

From 3D point‐cloud data to explainable geometric deep learning: State‐of‐the‐art and future challenges

Saranti, A., Pfeifer, B., Gollob, C., Stampfer, K., & Holzinger, A. (2024) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1554 · Cited by 24

Extend Your Own Correspondences: Unsupervised Distant Point Cloud Registration by Progressive Distance Extension

Liu, Q., Zhu, H., Wang, Z., Zhou, Y., Chang, S., & Guo, M. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.01967 · Cited by 24

LiveHPS: LiDAR-Based Scene-Level Human Pose and Shape Estimation in Free Environment

Ren, Y., Han, X., Zhao, C., Wang, J., Xu, L., Jingyi Yu, A., & Ma, Y. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.00128 · Cited by 24

Unsupervised Domain Adaptation for LiDAR Panoptic Segmentation

Bešić, B., Gosala, N., Cattaneo, D., & Valada, A. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3147326 · Cited by 24

A survey on weakly supervised 3D point cloud semantic segmentation

Wang, J., Liu, Y., Tan, H., & Zhang, M. (2023) · IET Computer Vision · doi:10.1049/cvi2.12250 · Cited by 23

Target-adaptive optical phased array lidar

Fu, Y., Chen, B., Yue, W., Tao, M., Zhao, H., Li, Y., Li, X., Qu, H., Li, X., Hu, X., et al. (2024) · Photonics Research · doi:10.1364/prj.514468 · Cited by 23

The Road to Safety: A Review of Uncertainty and Applications to Autonomous Driving Perception

Araújo, B., Teixeira, J. F., Fonseca, J., Cerqueira, R., & Beco, S. C. (2024) · Entropy · doi:10.3390/e26080634 · Cited by 28

TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards

Cheng, D., Cladera, F., Prabhu, A., Liu, X., Zhu, A., Green, P. C., Ehsani, R. J., Chaudhari, P., & Kumar, V. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10611103 · Cited by 23

WildScenes: A benchmark for 2D and 3D semantic segmentation in large-scale natural environments

Vidanapathirana, K., Knights, J., Hausler, S., Cox, M., Ramezani, M., Jooste, J., Griffiths, E., Mohamed, S., Sridharan, S., Fookes, C., et al. (2024) · The International Journal of Robotics Research · doi:10.1177/02783649241278369 · Cited by 29

SemCity: Semantic Scene Generation with Triplane Diffusion

Lee, J., Lee, S., Jo, C., Im, W., Seon, J., & Yoon, S. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02677 · Cited by 33

CMRNext: Camera to LiDAR Matching in the Wild for Localization and Extrinsic Calibration

Cattaneo, D., & Valada, A. (2025) · IEEE Transactions on Robotics · doi:10.1109/tro.2025.3546784 · Cited by 28

DeepTemporalSeg: Temporally Consistent Semantic Segmentation of 3D LiDAR Scans

Dewan, A., & Burgard, W. (2020) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra40945.2020.9197193 · Cited by 23

An Efficient 3-D Point Cloud Place Recognition Approach Based on Feature Point Extraction and Transformer

Ye, T., Yan, X., Wang, S., Li, Y., & Zhou, F. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3209727 · Cited by 23

Neural Architecture Search for Dense Prediction Tasks in Computer Vision

Mohan, R., Elsken, T., Zela, A., Metzen, J. H., Staffler, B., Brox, T., Valada, A., & Hutter, F. (2023) · International Journal of Computer Vision · doi:10.1007/s11263-023-01785-y · Cited by 25

Instant Domain Augmentation for LiDAR Semantic Segmentation

Ryu, K., Hwang, S., & Park, J. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00902 · Cited by 23

Multi-sensor fusion for robust localization with moving object segmentation in complex dynamic 3D scenes

Li, Q., Zhuang, Y., & Huai, J. (2023) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2023.103507 · Cited by 23

Triplet-Graph: Global Metric Localization Based on Semantic Triplet Graph for Autonomous Vehicles

Ma, W., Huang, S., & Sun, Y. (2024) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2024.3358752 · Cited by 23

Automating construction of road digital twin geometry using context and location aware segmentation

Davletshina, D., Reja, V. K., & Brilakis, I. (2024) · Automation in Construction · doi:10.1016/j.autcon.2024.105795 · Cited by 23

Shooting Labels: 3D Semantic Labeling by Virtual Reality

Ramirez, P. Z., Paternesi, C., Luigi, L. D., Lella, L. D., Gregorio, D. D., & Stefano, L. D. (2020) · IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) · doi:10.1109/aivr50618.2020.00027 · Cited by 23

ECM-OPCC: Efficient Context Model for Octree-Based Point Cloud Compression

Jin, Y., Zhu, Z., Xu, T., Lin, Y., & Wang, Y. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10446374 · Cited by 26

Point-MPP: Point Cloud Self-Supervised Learning From Masked Position Prediction

Fan, S., Gao, W., & Li, G. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3479309 · Cited by 23

Developments in 3-D Object Detection for Autonomous Driving: A Review

Wang, Y., Wang, S., Li, Y., & Liu, M. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3562284 · Cited by 22

Up-to-Down Network: Fusing Multi-Scale Context for 3D Semantic Scene Completion

Zou, H., Yang, X., Huang, T., Zhang, C., Liu, Y., Li, W., Wen, F., & Zhang, H. (2021) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9635888 · Cited by 22

Efficient LiDAR-based In-water Obstacle Detection and Segmentation by Autonomous Surface Vehicles in Aquatic Environments

Jeong, M., & Li, A. Q. (2021) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9636028 · Cited by 22

Deep Learning-Based Frameworks for Semantic Segmentation of Road Scenes

Alokasi, H., & Ahmad, M. B. (2022) · Electronics · doi:10.3390/electronics11121884 · Cited by 23

FinnWoodlands Dataset

Lagos, J., Lempiö, U., & Rahtu, E. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-31435-3_7 · Cited by 24

Adversarial Obstacle Generation Against LiDAR-Based 3D Object Detection

Wang, J., Li, F., Zhang, X., & Sun, H. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3302018 · Cited by 22

Cross-modal Unsupervised Domain Adaptation for 3D Semantic Segmentation via Bidirectional Fusion-then-Distillation

Wu, Y., Xing, M., Zhang, Y., Xie, Y., Jianping Fan, B., Shi, Z., & Qu, Y. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612013 · Cited by 22

3D Segmentation of Humans in Point Clouds with Synthetic Data

Takmaz, A., Schult, J., Kaftan, I., Akçay, M., Leibe, B., Sumner, R. W., Engelmann, F., & Tang, S. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00125 · Cited by 27

LiDAR-Camera Panoptic Segmentation via Geometry-Consistent and Semantic-Aware Alignment

Zhang, Z., Zhang, Z., Yu, Q., Yi, R., Xie, Y., & Ma, L. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00339 · Cited by 24

Deep Semantic Graph Matching for Large-Scale Outdoor Point Cloud Registration

Liu, S., Wang, T., Zhang, Y., Zhou, R., Li, L., Dai, C., Zhang, Y., Wang, L., & Wang, H. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3355707 · Cited by 22

WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting

Chen, K., Ge, R., Qiu, H., Ai-Rfou, R., Qi, C. R., Zhou, X., Yang, Z., Ettinger, S. M., Sun, P., Leng, Z., et al. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10610651 · Cited by 22

Annotation Tool and Urban Dataset for 3D Point Cloud Semantic Segmentation

Ibrahim, M. M., Akhtar, N., Wise, M. J., & Mian, A. S. (2021) · IEEE Access · doi:10.1109/access.2021.3062547 · Cited by 22

The Fusion Strategy of 2D and 3D Information Based on Deep Learning: A Review

Zhao, J., Wang, Y., Cao, Y., Guo, M., Huang, X., Zhang, R., Dou, X., Niu, X., Cui, Y., & Wang, J. (2021) · Remote Sensing · doi:10.3390/rs13204029 · Cited by 22

Occupancy Grid Generation With Dynamic Obstacle Segmentation in Stereo Images

Shepel, I. O., Adeshkin, V., Belkin, I., & Yudin, D. A. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3133799 · Cited by 22

DRINet++: Efficient Voxel-as-point Point Cloud SegmentationPreprint

Ye, M., Wan, R., Xu, S., Cao, T., & Chen, Q. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.08318 · Cited by 22

An efficient point cloud place recognition approach based on transformer in dynamic environment

Li, Q., Zhuang, Y., Huai, J., Chen, Y., & Yılmaz, A. (2023) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2023.11.013 · Cited by 21

Real-Time Multi-Modal Semantic Fusion on Unmanned Aerial Vehicles

Bultmann, S., Quenzel, J., & Behnke, S. (2021) · European Conference on Mobile Robots · doi:10.1109/ecmr50962.2021.9568812 · Cited by 21

Road-Model-Based Road Boundary Extraction for High Definition Map via LIDAR

Xiong, H., Zhu, T., Liu, Y., Pan, Y., Wu, S., & Chen, L. F. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3153689 · Cited by 21

SemanticFlow: Semantic Segmentation of Sequential LiDAR Point Clouds From Sparse Frame Annotations

Zhao, J., Huang, W., Wu, H. Y., Wen, C., Yang, B., Guo, Y., & Wang, C. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3264102 · Cited by 21

Novel Class Discovery for 3D Point Cloud Semantic Segmentation

Riz, L., Saltori, C., Ricci, E., & Poiesi, F. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00906 · Cited by 21

Circular Accessible Depth: A Robust Traversability Representation for UGV Navigation

Xie, S., Song, R., Zhao, Y., Huang, X., Li, Y., & Zhang, W. (2023) · IEEE Transactions on Robotics · doi:10.1109/tro.2023.3308780 · Cited by 21

Robust 3D Semantic Segmentation Based on Multi-Phase Multi-Modal Fusion for Intelligent Vehicles

Ni, P., Li, X., Xu, W., Kong, D., Hu, Y., & Wei, K. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3317784 · Cited by 21

A Comprehensive Framework for 3D Occupancy Estimation in Autonomous Driving

Gan, W., Mo, N., Xu, H., & Yokoya, N. (2024) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2024.3403134 · Cited by 44

CL-fusionBEV: 3D object detection method with camera-LiDAR fusion in Bird’s Eye View

Shi, P., Liu, Z., Dong, X., & Yang, A. (2024) · Complex & Intelligent Systems · doi:10.1007/s40747-024-01567-0 · Cited by 21

InverseMatrixVT3D: An Efficient Projection Matrix-Based Approach for 3D Occupancy Prediction

Ming, Z., Berrío, J. S., Shan, M., & Worrall, S. (2024) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros58592.2024.10802434 · Cited by 21

A training dataset for semantic segmentation of urban point cloud map for intelligent vehicles

Song, H., Jo, K., Cho, J., Son, Y., Kim, C.-S., & Han, K.-J. (2022) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2022.02.007 · Cited by 21

Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking

Jing, L., Yu, R., Kretzschmar, H., Li, K., Qi, C. R., Zhao, H., Ayvacı, A., Chen, X., Cower, D., Li, Y., et al. (2022) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra46639.2022.9811749 · Cited by 22

VPA-Net: A visual perception assistance network for 3d lidar semantic segmentation

Lin, F., Lin, T., Yao, Y. C., Ren, H., Wu, J., & Cai, Q. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.111014 · Cited by 20

Overview of Terrain Traversability Evaluation for Autonomous Robots

Shu, Y., Dong, L., Liu, J., Liu, C., & Wei, W. (2024) · Journal of Field Robotics · doi:10.1002/rob.22461 · Cited by 20

Unstructured Road Segmentation Based on Road Boundary Enhancement Point-Cylinder Network Using LiDAR Sensor

Zhu, Z., Xu, L., Xu, J., Yuan, J., & Tao, J. (2021) · Remote Sensing · doi:10.3390/rs13030495 · Cited by 20

LiDAR Odometry and Mapping Based on Semantic Information for Outdoor Environment

Du, S., Li, Y., Li, X., & Wu, M. (2021) · Remote Sensing · doi:10.3390/rs13152864 · Cited by 20

Contrastive Instance Association for 4D Panoptic Segmentation Using Sequences of 3D LiDAR Scans

Marcuzzi, R., Nunes, L., Wiesmann, L., Vizzo, I., Behley, J., & Stachniss, C. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3140439 · Cited by 20

Fused Projection-Based Point Cloud Segmentation

Kellner, M., Stahl, B., & Reiterer, A. (2022) · Sensors · doi:10.3390/s22031139 · Cited by 20

3D-Pruning: A Model Compression Framework for Efficient 3D Action Recognition

Guo, J., Liu, J., & Xu, D. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3197395 · Cited by 20

Crossmodal Few-shot 3D Point Cloud Semantic Segmentation

Zhao, Z., Wu, Z., Wu, X., Zhang, C., & Wang, S. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548251 · Cited by 20

HD-CCSOM: Hierarchical and Dense Collaborative Continuous Semantic Occupancy Mapping through Label Diffusion

Deng, Y., Wang, M., Yang, Y. M., & Yue, Y. (2022) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros47612.2022.9981756 · Cited by 20

Cross-Modal Contrastive Learning for Domain Adaptation in 3D Semantic Segmentation

Xing, B., Ying, X., Wang, R., Yang, J., & Chen, T. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i3.25400 · Cited by 22

CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Clouds

Li, E., Razani, R., Xu, Y., & Liu, B. (2023) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48891.2023.10160705 · Cited by 20

2D-3D Interlaced Transformer for Point Cloud Segmentation with Scene-Level Supervision

Yang, C.-K., Chen, M.-H., Chuang, Y., & Lin, Y. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00096 · Cited by 20

MemorySeg: Online LiDAR Semantic Segmentation with a Latent Memory

Li, E., Casas, S., & Urtasun, R. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00075 · Cited by 20

Sequential Point Clouds: A Survey

Wang, H., & Tian, Y. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3365970 · Cited by 23

H2GFormer: Horizontal-to-Global Voxel Transformer for 3D Semantic Scene Completion

Wang, Y., & Tong, C. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i6.28384 · Cited by 20

SCP: Spherical-Coordinate-Based Learned Point Cloud Compression

Luo, A., Song, L., Nonaka, K., Unno, K., Sun, H., Goto, M., & Katto, J. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i4.28188 · Cited by 20

APPFNet: Adaptive point-pixel fusion network for 3D semantic segmentation with neighbor feature aggregation

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