Cover Image

3D Can Be Explored In 2D: Pseudo-Label Generation for LiDAR Point Clouds Using Sensor-Intensity-Based 2D Semantic Segmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Caunes, Andrew, Chateau, Thierry, Frémont, Vincent
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multi-View Projection for Unsupervised Domain Adaptation in 3D Semantic Segmentation
by: Caunes, Andrew, et al.
Published: (2025)

FreeOcc: Training-free Panoptic Occupancy Prediction via Foundation Models
by: Caunes, Andrew, et al.
Published: (2026)

Label-Efficient LiDAR Semantic Segmentation with 2D-3D Vision Transformer Adapters
by: Hindel, Julia, et al.
Published: (2025)

Image-Guided Semantic Pseudo-LiDAR Point Generation for 3D Object Detection
by: Lee, Minseung, et al.
Published: (2024)

LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object Detection
by: Fang, Jin, et al.
Published: (2023)

Unsupervised Domain Adaptation for 3D LiDAR Semantic Segmentation Using Contrastive Learning and Multi-Model Pseudo Labeling
by: Kaushik, Abhishek, et al.
Published: (2025)

Label-Efficient Semantic Segmentation of LiDAR Point Clouds in Adverse Weather Conditions
by: Piroli, Aldi, et al.
Published: (2024)

3D Learnable Supertoken Transformer for LiDAR Point Cloud Scene Segmentation
by: Lu, Dening, et al.
Published: (2024)

Off-Road LiDAR Intensity Based Semantic Segmentation
by: Viswanath, Kasi, et al.
Published: (2024)

SegNet4D: Efficient Instance-Aware 4D Semantic Segmentation for LiDAR Point Cloud
by: Wang, Neng, et al.
Published: (2024)

Audio Array-Based 3D UAV Trajectory Estimation with LiDAR Pseudo-Labeling
by: Lei, Allen, et al.
Published: (2024)

On the Impact of LiDAR Point Cloud Compression on Remote Semantic Segmentation
by: Fernandes, Tiago de S., et al.
Published: (2025)

HeLiMOS: A Dataset for Moving Object Segmentation in 3D Point Clouds From Heterogeneous LiDAR Sensors
by: Lim, Hyungtae, et al.
Published: (2024)

Explainable LiDAR 3D Point Cloud Segmentation and Clustering for Detecting Airplane-Generated Wind Turbulence
by: Qu, Zhan, et al.
Published: (2025)

SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Clouds
by: Wang, Yanbo, et al.
Published: (2024)

Enhancing 3D LiDAR Segmentation by Shaping Dense and Accurate 2D Semantic Predictions
by: Dong, Xiaoyu, et al.
Published: (2026)

Semantics-Guided Moving Object Segmentation with 3D LiDAR
by: Gu, Shuo, et al.
Published: (2022)

Self-supervised Learning of LiDAR 3D Point Clouds via 2D-3D Neural Calibration
by: Zhang, Yifan, et al.
Published: (2024)

D-PLS: Decoupled Semantic Segmentation for 4D-Panoptic-LiDAR-Segmentation
by: Steinhauser, Maik, et al.
Published: (2025)

Contextual Range-View Projection for 3D LiDAR Point Clouds
by: Mousavi, Seyedali, et al.
Published: (2026)

LinK3D: Linear Keypoints Representation for 3D LiDAR Point Cloud
by: Cui, Yunge, et al.
Published: (2022)

End-to-end 2D-3D Registration between Image and LiDAR Point Cloud for Vehicle Localization
by: Wang, Guangming, et al.
Published: (2023)

Exploring Single Domain Generalization of LiDAR-based Semantic Segmentation under Imperfect Labels
by: Kong, Weitong, et al.
Published: (2025)

ForestFormer3D: A Unified Framework for End-to-End Segmentation of Forest LiDAR 3D Point Clouds
by: Xiang, Binbin, et al.
Published: (2025)

LiDAR-EVS: Enhance Extrapolated View Synthesis for 3D Gaussian Splatting with Pseudo-LiDAR Supervision
by: Huang, Yiming, et al.
Published: (2026)

RENO: Real-Time Neural Compression for 3D LiDAR Point Clouds
by: You, Kang, et al.
Published: (2025)

PCTreeS: 3D Point Cloud Tree Species Classification Using Airborne LiDAR Images
by: Lin, Hongjin, et al.
Published: (2024)

Text2LiDAR: Text-guided LiDAR Point Cloud Generation via Equirectangular Transformer
by: Wu, Yang, et al.
Published: (2024)

Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation
by: Zheng, Yu, et al.
Published: (2023)

LiLa-Net: Lightweight Latent LiDAR Autoencoder for 3D Point Cloud Reconstruction
by: Resino, Mario, et al.
Published: (2025)

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting
by: Jiang, Junzhe, et al.
Published: (2025)

Mixed Signals: A Diverse Point Cloud Dataset for Heterogeneous LiDAR V2X Collaboration
by: Luo, Katie Z, et al.
Published: (2025)

Systematic Evaluation of Depth Backbones and Semantic Cues for Monocular Pseudo-LiDAR 3D Detection
by: Ajadalu, Samson Oseiwe
Published: (2026)

Towards Explainable LiDAR Point Cloud Semantic Segmentation via Gradient Based Target Localization
by: Kuriyal, Abhishek, et al.
Published: (2024)

Sparse Points to Dense Clouds: Enhancing 3D Detection with Limited LiDAR Data
by: Kumar, Aakash, et al.
Published: (2024)

LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection
by: Zhou, Sifan, et al.
Published: (2024)

GSeg3D: A High-Precision Grid-Based Algorithm for Safety-Critical Ground Segmentation in LiDAR Point Clouds
by: Lodhi, Muhammad Haider Khan, et al.
Published: (2026)

NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields
by: Zhang, Junge, et al.
Published: (2023)

3D-AVS: LiDAR-based 3D Auto-Vocabulary Segmentation
by: Wei, Weijie, et al.
Published: (2024)

LiM-Loc: Visual Localization with Dense and Accurate 3D Reference Maps Directly Corresponding 2D Keypoints to 3D LiDAR Point Clouds
by: Tsuji, Masahiko, et al.
Published: (2025)