CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving
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Abstract (arXiv)
Accurate and fast scene understanding is one of the challenging task for autonomous driving, which requires to take full advantage of LiDAR point clouds for semantic segmentation. In this paper, we present a concise and efficient image-based semantic segmentation network, named CENet. In order to improve the descriptive power of learned features and reduce the computational as well as time complexity, our CENet integrates the convolution with larger kernel size instead of MLP, carefully-selected activation functions, and multiple auxiliary segmentation heads with corresponding loss functions into architecture. Quantitative and qualitative experiments conducted on publicly available benchmarks, SemanticKITTI and SemanticPOSS, demonstrate that our pipeline achieves much better mIoU and inference performance compared with state-of-the-art models. The code will be available at https://github.com/huixiancheng/CENet.
Key facts. Cited by 56 papers in the map (data through 14 Oct 2026). Builds on 22 of its 24 references that are in the map. First posted on arXiv 26 Jul 2022.
Builds on
22 of 24 references.
References · 22
- 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
- 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
- 2019KPConv: Flexible and Deformable Convolution for Point Cloudscited by 1,205
- 20173D Semantic Segmentation with Submanifold Sparse Convolutional Networkscited by 748
- 2019RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Cloudscited by 585
- 2019Deep Learning for 3D Point Clouds: A Surveycited by 558
- 2021RepVGG: Making VGG-style ConvNets Great Againcited by 522
- 2020Searching Efficient 3D Architectures with Sparse Point-Voxel Convolutioncited by 423
- 2019Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challengescited by 314
- 2017SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloudcited by 232
- 2018SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloudcited by 228
- 2020SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Drivingcited by 226
10 more
- 2020SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentationcited by 170
- 2021RangeDet:In Defense of Range View for LiDAR-based 3D Object Detectioncited by 140
- 2020SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instancescited by 123
- 2020Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentationcited by 112
- 2021Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusioncited by 72
- 2020KPRNet: Improving projection-based LiDAR semantic segmentationcited by 47
- 2021FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decodingcited by 46
- 2020Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platformcited by 40
- 2021Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutionscited by 37
- 2020Multi Projection Fusion for Real-time Semantic Segmentation of 3D LiDAR Point Cloudscited by 24
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Citing papers per year: 2022: 2; 2023: 16; 2024: 16; 2025: 19; 2026: 3.
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- 2023Robo3D: Towards Robust and Reliable 3D Perception against Corruptionscited by 129
- 2023Rethinking Range View Representation for LiDAR Segmentationcited by 128
- 2023Segment Any Point Cloud Sequences by Distilling Vision Foundation Modelscited by 125
- 2023MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Drivingcited by 68
- 2023UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebasecited by 57
- 2023FRNet: Frustum-Range Networks for Scalable LiDAR Segmentationcited by 50
- 2024RangeLDM: Fast Realistic LiDAR Point Cloud Generationcited by 47
- 20244D Contrastive Superflows are Dense 3D Representation Learnerscited by 33
- 2024Is Your LiDAR Placement Optimized for 3D Scene Understanding?cited by 26
- 2022Domain generalization of 3D semantic segmentation in autonomous drivingcited by 25
- 2024Multi-Space Alignments Towards Universal LiDAR Segmentationcited by 25
- 2024Centering the Value of Every Modality: Towards Efficient and Resilient Modality-agnostic Semantic Segmentationcited by 22
38 more
- 2023Benchmarking the Robustness of LiDAR Semantic Segmentation Modelscited by 18
- 2023TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentationcited by 13
- 2024An Empirical Study of Training State-of-the-Art LiDAR Segmentation Modelscited by 12
- 2024MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selectioncited by 12
- 2025LargeAD: Large-Scale Cross-Sensor Data Pretraining for Autonomous Drivingcited by 12
- 20253EED: Ground Everything Everywhere in 3Dcited by 12
- 2024Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understandingcited by 11
- 2024ECLAIR: A High-Fidelity Aerial LiDAR Dataset for Semantic Segmentationcited by 10
- 2025SPIRAL: Semantic-Aware Progressive LiDAR Scene Generation and Understandingcited by 10
- 2024Reflectivity Is All You Need!: Advancing LiDAR Semantic Segmentationcited by 9
- 2023Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentationcited by 7
- 2023Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentationcited by 6
- 2023CurveCloudNet: Processing Point Clouds with 1D Structurecited by 5
- 2023ParisLuco3D: A high-quality target dataset for domain generalization of LiDAR perceptioncited by 5
- 2024Fine-grained Image-to-LiDAR Contrastive Distillation with Visual Foundation Modelscited by 5
- 2025NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic Segmentationcited by 5
- 2024Small, Versatile and Mighty: A Range-View Perception Frameworkcited by 4
- 2024Filling Missing Values Matters for Range Image-Based Point Cloud Segmentationcited by 4
- 2024Exploiting Local Features and Range Images for Small Data Real-Time Point Cloud Semantic Segmentationcited by 4
- 2022PCB-RandNet: Rethinking Random Sampling for LIDAR Semantic Segmentation in Autonomous Driving Scenecited by 3
- 2025FLARES: Fast and Accurate LiDAR Multi-Range Semantic Segmentationcited by 3
- 2025HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Drivingcited by 3
- 2023Revisiting Multi-modal 3D Semantic Segmentation in Real-world Autonomous Drivingcited by 2
- 2024Trainable Pointwise Decoder Module for Point Cloud Segmentationcited by 2
- 2025SN-LiDAR: Semantic Neural Fields for Novel Space-time View LiDAR Synthesiscited by 2
- 2025Real Time Semantic Segmentation of High Resolution Automotive LiDAR Scanscited by 2
- 2023TransUPR: A Transformer-based Uncertain Point Refiner for LiDAR Point Cloud Semantic Segmentationcited by 1
- 2024Learning from Spatio-temporal Correlation for Semi-Supervised LiDAR Semantic Segmentationcited by 1
- 2025HexPlane Representation for 3D Semantic Scene Understandingcited by 1
- 2025LiDAR Based Semantic Perception for Forklifts in Outdoor Environmentscited by 1
- 2025HARP-NeXt: High-Speed and Accurate Range-Point Fusion Network for 3D LiDAR Semantic Segmentationcited by 1
- 2023LENet: Lightweight And Efficient LiDAR Semantic Segmentation Using Multi-Scale Convolution Attentioncited by 0
- 2023Instance-aware 3D Semantic Segmentation powered by Shape Generators and Classifierscited by 0
- 20254D-CS: Exploiting Cluster Prior for 4D Spatio-Temporal LiDAR Semantic Segmentationcited by 0
- 2025An Experimental Study of SOTA LiDAR Segmentation Modelscited by 0
- 2025Depth-Aware Range Image-Based Model for Point Cloud Segmentationcited by 0
- 2025A Data-Centric Approach to 3D Semantic Segmentation of Railway Scenescited by 0
- 2025Towards Generalized Range-View LiDAR Segmentation in Adverse Weathercited by 0
50 most cited of 56 All 56 (JSON)
- 2026Adversarially Guided Diffusion for LiDAR Range Image Synthesis8 Jul 2026
- 2026Semantic Occupancy Prediction with Dual Range-Voxel Representation30 Jun 2026
- 2026Learning to Identify Out-of-Distribution Objects for 3D LiDAR Anomaly Segmentation26 Apr 2026
- 20253EED: Ground Everything Everywhere in 3D3 Nov 2025
- 2025BikeScenes: LiDAR Semantic Segmentation for Bicycles29 Oct 2025
- 2025DAGLFNet: Deep Feature Attention Guided Global and Local Feature Fusion for Pseudo-Image Point Cloud Segmentation12 Oct 2025
- 2025HARP-NeXt: High-Speed and Accurate Range-Point Fusion Network for 3D LiDAR Semantic Segmentation8 Oct 2025
- 2025RangeSAM: On the Potential of Visual Foundation Models for Range-View represented LiDAR segmentation19 Sep 2025
- 2025Towards Generalized Range-View LiDAR Segmentation in Adverse Weather10 Jun 2025
- 2025NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic Segmentation30 May 2025
- 2025SPIRAL: Semantic-Aware Progressive LiDAR Scene Generation and Understanding28 May 2025
- 2025LiDAR Based Semantic Perception for Forklifts in Outdoor Environments28 May 2025
38 more
- 2025Real Time Semantic Segmentation of High Resolution Automotive LiDAR Scans30 Apr 2025
- 2025A Data-Centric Approach to 3D Semantic Segmentation of Railway Scenes25 Apr 2025
- 2025SN-LiDAR: Semantic Neural Fields for Novel Space-time View LiDAR Synthesis11 Apr 2025
- 2025HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Driving22 Mar 2025
- 2025Depth-Aware Range Image-Based Model for Point Cloud Segmentation19 Mar 2025
- 2025HexPlane Representation for 3D Semantic Scene Understanding7 Mar 2025
- 2025An Experimental Study of SOTA LiDAR Segmentation Models18 Feb 2025
- 2025FLARES: Fast and Accurate LiDAR Multi-Range Semantic Segmentation13 Feb 2025
- 2025LargeAD: Large-Scale Cross-Sensor Data Pretraining for Autonomous Driving7 Jan 2025
- 20254D-CS: Exploiting Cluster Prior for 4D Spatio-Temporal LiDAR Semantic Segmentation6 Jan 2025
- 2024MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selection22 Dec 2024
- 2024Exploiting Local Features and Range Images for Small Data Real-Time Point Cloud Semantic Segmentation14 Oct 2024
- 2024Learning from Spatio-temporal Correlation for Semi-Supervised LiDAR Semantic Segmentation9 Oct 2024
- 2024Trainable Pointwise Decoder Module for Point Cloud Segmentation2 Aug 2024
- 2024Centering the Value of Every Modality: Towards Efficient and Resilient Modality-agnostic Semantic Segmentation16 Jul 2024
- 20244D Contrastive Superflows are Dense 3D Representation Learners8 Jul 2024
- 2024An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models23 May 2024
- 2024Fine-grained Image-to-LiDAR Contrastive Distillation with Visual Foundation Models23 May 2024
- 2024Filling Missing Values Matters for Range Image-Based Point Cloud Segmentation16 May 2024
- 2024Multi-Space Alignments Towards Universal LiDAR Segmentation2 May 2024
- 2024ECLAIR: A High-Fidelity Aerial LiDAR Dataset for Semantic Segmentation16 Apr 2024
- 2024Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding25 Mar 2024
- 2024Is Your LiDAR Placement Optimized for 3D Scene Understanding?25 Mar 2024
- 2024Reflectivity Is All You Need!: Advancing LiDAR Semantic Segmentation19 Mar 2024
- 2024RangeLDM: Fast Realistic LiDAR Point Cloud Generation15 Mar 2024
- 2024Small, Versatile and Mighty: A Range-View Perception Framework1 Mar 2024
- 2023Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation12 Dec 2023
- 2023FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation7 Dec 2023
- 2023Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation29 Nov 2023
- 2023Instance-aware 3D Semantic Segmentation powered by Shape Generators and Classifiers21 Nov 2023
- 2023ParisLuco3D: A high-quality target dataset for domain generalization of LiDAR perception25 Oct 2023
- 2023Revisiting Multi-modal 3D Semantic Segmentation in Real-world Autonomous Driving13 Oct 2023
- 2023TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentation14 Sep 2023
- 2023UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase11 Sep 2023
- 2023Segment Any Point Cloud Sequences by Distilling Vision Foundation Models15 Jun 2023
- 2023Robo3D: Towards Robust and Reliable 3D Perception against Corruptions30 Mar 2023
- 2023CurveCloudNet: Processing Point Clouds with 1D Structure21 Mar 2023
- 2023MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Driving15 Mar 2023
50 newest of 56 All 56 (JSON)
- 2023Rethinking Range View Representation for LiDAR Segmentationcited by 128
- 2024RangeLDM: Fast Realistic LiDAR Point Cloud Generationcited by 47
- 2025SPIRAL: Semantic-Aware Progressive LiDAR Scene Generation and Understandingcited by 10
- 2026Adversarially Guided Diffusion for LiDAR Range Image Synthesiscited by 0
- 2026Adversarially Guided Diffusion for LiDAR Range Image Synthesis8 Jul 2026
- 2025SPIRAL: Semantic-Aware Progressive LiDAR Scene Generation and Understanding28 May 2025
- 2024RangeLDM: Fast Realistic LiDAR Point Cloud Generation15 Mar 2024
- 2023Rethinking Range View Representation for LiDAR Segmentation9 Mar 2023
- 2023Robo3D: Towards Robust and Reliable 3D Perception against Corruptionscited by 129
- 2023Segment Any Point Cloud Sequences by Distilling Vision Foundation Modelscited by 125
- 2023MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Drivingcited by 68
- 2023UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebasecited by 57
- 2023FRNet: Frustum-Range Networks for Scalable LiDAR Segmentationcited by 50
- 20244D Contrastive Superflows are Dense 3D Representation Learnerscited by 33
- 2024Is Your LiDAR Placement Optimized for 3D Scene Understanding?cited by 26
- 2022Domain generalization of 3D semantic segmentation in autonomous drivingcited by 25
- 2024Multi-Space Alignments Towards Universal LiDAR Segmentationcited by 25
- 2024Centering the Value of Every Modality: Towards Efficient and Resilient Modality-agnostic Semantic Segmentationcited by 22
- 2023Benchmarking the Robustness of LiDAR Semantic Segmentation Modelscited by 18
- 2023TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentationcited by 13
12 most cited of 52 All 52 (JSON)
- 2026Semantic Occupancy Prediction with Dual Range-Voxel Representation30 Jun 2026
- 2026Learning to Identify Out-of-Distribution Objects for 3D LiDAR Anomaly Segmentation26 Apr 2026
- 20253EED: Ground Everything Everywhere in 3D3 Nov 2025
- 2025BikeScenes: LiDAR Semantic Segmentation for Bicycles29 Oct 2025
- 2025DAGLFNet: Deep Feature Attention Guided Global and Local Feature Fusion for Pseudo-Image Point Cloud Segmentation12 Oct 2025
- 2025HARP-NeXt: High-Speed and Accurate Range-Point Fusion Network for 3D LiDAR Semantic Segmentation8 Oct 2025
- 2025RangeSAM: On the Potential of Visual Foundation Models for Range-View represented LiDAR segmentation19 Sep 2025
- 2025Towards Generalized Range-View LiDAR Segmentation in Adverse Weather10 Jun 2025
- 2025NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic Segmentation30 May 2025
- 2025LiDAR Based Semantic Perception for Forklifts in Outdoor Environments28 May 2025
- 2025Real Time Semantic Segmentation of High Resolution Automotive LiDAR Scans30 Apr 2025
- 2025A Data-Centric Approach to 3D Semantic Segmentation of Railway Scenes25 Apr 2025
12 newest of 52 All 52 (JSON)