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Real-Time LiDAR Point Cloud Semantic Segmentation for Autonomous Driving

https://doi.org/10.3390/electronics11010011

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-01261-8_20openalex-snapshot

BiSeNet: Bilateral Segmentation Network for Real-Time Semantic Segmentation

inferredcites →https://doi.org/10.1007/978-3-030-58604-1_1openalex-snapshot

SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation

inferredcites →https://doi.org/10.1007/978-3-030-64559-5_16openalex-snapshot

SalsaNext: Fast, Uncertainty-Aware Semantic Segmentation of LiDAR Point Clouds

inferredcites →https://doi.org/10.1109/3dv.2018.00053openalex-snapshot

Efficient Convolutions for Real-Time Semantic Segmentation of 3D Point Clouds

inferredcites →https://doi.org/10.1109/access.2020.3045681openalex-snapshot

DepthNet: Real-Time LiDAR Point Cloud Depth Completion for Autonomous Vehicles

inferredcites →https://doi.org/10.1109/aspdac.2018.8297347openalex-snapshot

Optimizing FPGA-based convolutional neural networks accelerator for image super-resolution

inferredcites →https://doi.org/10.1109/cvpr.2012.6248074openalex-snapshot

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

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.691openalex-snapshot

Multi-view 3D Object Detection Network for Autonomous Driving

inferredcites →https://doi.org/10.1109/cvpr.2018.00268openalex-snapshot

SPLATNet: Sparse Lattice Networks for Point Cloud Processing

inferredcites →https://doi.org/10.1109/cvpr.2018.00409openalex-snapshot

Tangent Convolutions for Dense Prediction in 3D

inferredcites →https://doi.org/10.1109/cvpr.2018.00464openalex-snapshot

The Lovasz-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks

inferredcites →https://doi.org/10.1109/cvpr.2018.00472openalex-snapshot

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2018.00479openalex-snapshot

Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00962openalex-snapshot

PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation

inferredcites →https://doi.org/10.1109/cvpr42600.2020.01112openalex-snapshot

RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

inferredcites →https://doi.org/10.1109/cvpr42600.2020.01164openalex-snapshot

nuScenes: A Multimodal Dataset for Autonomous Driving

inferredcites →https://doi.org/10.1109/fpt.2010.5681769openalex-snapshot

High performance and memory efficient implementation of matrix multiplication on FPGAs

inferredcites →https://doi.org/10.1109/iccv.2017.99openalex-snapshot

Escape from Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models

inferredcites →https://doi.org/10.1109/iccv.2019.00939openalex-snapshot

SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

inferredcites →https://doi.org/10.1109/icra.2018.8462926openalex-snapshot

SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

inferredcites →https://doi.org/10.1109/icra.2019.8793495openalex-snapshot

SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

inferredcites →https://doi.org/10.1109/iros.2018.8594049openalex-snapshot

Joint 3D Proposal Generation and Object Detection from View Aggregation

inferredcites →https://doi.org/10.1109/iros40897.2019.8967762openalex-snapshot

RangeNet ++: Fast and Accurate LiDAR Semantic Segmentation

inferredcites →https://doi.org/10.1109/iscas.2018.8351244openalex-snapshot

Real-Time Road Segmentation Using LiDAR Data Processing on an FPGA

inferredcites →https://doi.org/10.1109/iscas.2018.8351474openalex-snapshot

Towards a Multi-array Architecture for Accelerating Large-scale Matrix Multiplication on FPGAs

inferredcites →https://doi.org/10.1109/iv47402.2020.9304694openalex-snapshot

SalsaNet: Fast Road and Vehicle Segmentation in LiDAR Point Clouds for Autonomous Driving

inferredcites →https://doi.org/10.1109/tcsi.2018.2881162openalex-snapshot

ChipNet: Real-Time LiDAR Processing for Drivable Region Segmentation on an FPGA

inferredcites →https://doi.org/10.1109/tcsi.2020.3038139openalex-snapshot

RoadNet-RT: High Throughput CNN Architecture and SoC Design for Real-Time Road Segmentation

inferredcites →https://doi.org/10.1109/tits.2019.2905046openalex-snapshot

3D LiDAR-Based Global Localization Using Siamese Neural Network

inferredcites →https://doi.org/10.1109/tpami.2016.2572683openalex-snapshot

Fully Convolutional Networks for Semantic Segmentation

inferredcites →https://doi.org/10.1145/3326362openalex-snapshot

Dynamic Graph CNN for Learning on Point Clouds

inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-snapshot

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

inferredcites →https://doi.org/10.48550/arxiv.1612.00593openalex-snapshot

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

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s11554-025-01643-9openalex-snapshot

FPGA implementation of double-head SalsaNext: a CNN-based model for LiDAR point cloud segmentation

inferred← citeshttps://doi.org/10.1007/s44196-024-00630-5openalex-snapshot

Channel2DTransformer: A Multi-level Features Self-attention Fusion Module for Semantic Segmentation

inferred← citeshttps://doi.org/10.1016/j.ipm.2026.105077openalex-snapshot

GRIP-Net: Graph Relational Interactive Prototype Network for few-shot point cloud semantic segmentation

inferred← citeshttps://doi.org/10.1016/j.neucom.2024.127625openalex-snapshot

Fast-DSAGCN: Enhancing semantic segmentation with multifaceted attention mechanisms

inferred← citeshttps://doi.org/10.1016/j.ophoto.2024.100061openalex-snapshot

Semantic segmentation of raw multispectral laser scanning data from urban environments with deep neural networks

inferred← citeshttps://doi.org/10.1016/j.seta.2025.104476openalex-snapshot

Autonomous vehicle integration with public transit for congestion mitigation and energy efficiency

inferred← citeshttps://doi.org/10.1080/15732479.2022.2136718openalex-snapshot

Adaptively unsupervised seepage detection in tunnels from 3D point clouds

inferred← citeshttps://doi.org/10.1109/access.2025.3528245openalex-snapshot

MFFTNet: A Novel 3D Point Cloud Segmentation Network Based on Multi-Scale Feature Fusion and Transformer Architecture

inferred← citeshttps://doi.org/10.1109/bigdata59044.2023.10386733openalex-snapshot

Unveiling the Road Matrix: Development of Versatile Pavement Surface Models from Low-resolution Aerial Images

inferred← citeshttps://doi.org/10.1109/ccdc58219.2023.10327436openalex-snapshot

LiDAR Point Cloud Semantic Segmentation Method Based on Multi-scale Contextual Feature

inferred← citeshttps://doi.org/10.1109/iccece61355.2025.10940080openalex-snapshot

Real-Time 3D LiDAR Point Cloud Data Acquisition & Generation on Jetson

inferred← citeshttps://doi.org/10.1109/icfsp62546.2024.10785465openalex-snapshot

Classifying Static and Dynamic Tracks for LiDAR-Based Navigation of Autonomous Vehicle Systems

inferred← citeshttps://doi.org/10.1109/iciea65512.2025.11148916openalex-snapshot

Enhancing Autonomous Vehicle Navigation and Perception with Advanced Light Detection and Ranging (LiDAR) sensing Data Processing and Anomaly Detection Techniques

inferred← citeshttps://doi.org/10.1109/ijcnn64981.2025.11227789openalex-snapshot

Autonomous Vehicle Localization via LiDAR-Based Classification of Dynamic and Static Tracks in Dynamic Environments

inferred← citeshttps://doi.org/10.1109/mits.2023.3325854openalex-snapshot

3D Lidar Point Cloud Segmentation for Automated Driving

inferred← citeshttps://doi.org/10.1109/tcad.2022.3197494openalex-snapshot

SENTunnel: Fast Path for Sensor Data Access on Automotive Embedded Systems

inferred← citeshttps://doi.org/10.1109/tiv.2024.3383599openalex-snapshot

Probabilistic Graph-Based Real-Time Ground Segmentation for Urban Robotics

inferred← citeshttps://doi.org/10.1109/vtc2025-spring65109.2025.11174498openalex-snapshot

Stream-Based LiDAR Point Cloud Ground Segmentation for Autonomous Vehicle

inferred← citeshttps://doi.org/10.32604/jai.2022.031235openalex-snapshot

Deep Learning-Based 3D Instance and Semantic Segmentation: A Review

inferred← citeshttps://doi.org/10.3389/frobt.2024.1341689openalex-snapshot

Implementation and analysis of a parallel kalman filter algorithm for lidar localization based on CUDA technology

inferred← citeshttps://doi.org/10.3390/app15095181openalex-snapshot

A Generative Model Approach for LiDAR-Based Classification and Ego Vehicle Localization Using Dynamic Bayesian Networks

inferred← citeshttps://doi.org/10.3390/electronics11060937openalex-snapshot

IE-Net: Information-Enhanced Binary Neural Networks for Accurate Classification

inferred← citeshttps://doi.org/10.3390/electronics12153228openalex-snapshot

Fast Context-Awareness Encoder for LiDAR Point Semantic Segmentation

inferred← citeshttps://doi.org/10.3390/electronics12183751openalex-snapshot

GPU-Accelerated Interaction-Aware Motion Prediction

inferred← citeshttps://doi.org/10.3390/electronics13153008openalex-snapshot

Overview of Pest Detection and Recognition Algorithms

inferred← citeshttps://doi.org/10.3390/s23010547openalex-snapshot

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

inferred← citeshttps://doi.org/10.3390/s23136119openalex-snapshot

Systematic and Comprehensive Review of Clustering and Multi-Target Tracking Techniques for LiDAR Point Clouds in Autonomous Driving Applications

inferred← citeshttps://doi.org/10.3390/signals6040053openalex-snapshot

Towards Next-Generation FPGA-Accelerated Vision-Based Autonomous Driving: A Comprehensive Review

inferred← citeshttps://doi.org/10.4271/2023-01-0740openalex-snapshot

Utilizing Neural Networks for Semantic Segmentation on RGB/LiDAR Fused Data for Off-road Autonomous Military Vehicle Perception

inferred← citeshttps://doi.org/10.5194/isprs-archives-xlviii-1-2024-887-2024openalex-snapshot

Weakly Supervised Learning Method for Semantic Segmentation of Large-Scale 3D Point Cloud Based on Transformers

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