Cover Image

Learning to Generate 4D LiDAR Sequences

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liang, Ao, Liu, Youquan, Yang, Yu, Lu, Dongyue, Li, Linfeng, Kong, Lingdong, Zhao, Huaici, Ooi, Wei Tsang
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Robotics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LiDARCrafter: Dynamic 4D World Modeling from LiDAR Sequences
by: Liang, Ao, et al.
Published: (2025)

Perspective-Invariant 3D Object Detection
by: Liang, Ao, et al.
Published: (2025)

U4D: Uncertainty-Aware 4D World Modeling from LiDAR Sequences
by: Xu, Xiang, et al.
Published: (2025)

La La LiDAR: Large-Scale Layout Generation from LiDAR Data
by: Liu, Youquan, et al.
Published: (2025)

Not All Points Are Equal: Uncertainty-Aware 4D LiDAR Scene Synthesis
by: Xu, Xiang, et al.
Published: (2026)

Veila: Panoramic LiDAR Generation from a Monocular RGB Image
by: Liu, Youquan, et al.
Published: (2025)

OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation
by: Liu, Youquan, et al.
Published: (2026)

SPIRAL: Semantic-Aware Progressive LiDAR Scene Generation and Understanding
by: Zhu, Dekai, et al.
Published: (2025)

Multi-Space Alignments Towards Universal LiDAR Segmentation
by: Liu, Youquan, et al.
Published: (2024)

FlexEvent: Towards Flexible Event-Frame Object Detection at Varying Operational Frequencies
by: Lu, Dongyue, et al.
Published: (2024)

Is Your LiDAR Placement Optimized for 3D Scene Understanding?
by: Li, Ye, et al.
Published: (2024)

OpenESS: Event-based Semantic Scene Understanding with Open Vocabularies
by: Kong, Lingdong, et al.
Published: (2024)

FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation
by: Xu, Xiang, et al.
Published: (2023)

EventFly: Event Camera Perception from Ground to the Sky
by: Kong, Lingdong, et al.
Published: (2025)

3EED: Ground Everything Everywhere in 3D
by: Li, Rong, et al.
Published: (2025)

An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models
by: Sun, Jiahao, et al.
Published: (2024)

LiMoE: Mixture of LiDAR Representation Learners from Automotive Scenes
by: Xu, Xiang, et al.
Published: (2025)

Visual Grounding from Event Cameras
by: Kong, Lingdong, et al.
Published: (2025)

Talk2Event: Grounded Understanding of Dynamic Scenes from Event Cameras
by: Kong, Lingdong, et al.
Published: (2025)

Enhanced Spatiotemporal Consistency for Image-to-LiDAR Data Pretraining
by: Xu, Xiang, et al.
Published: (2025)

3D and 4D World Modeling: A Survey
by: Kong, Lingdong, et al.
Published: (2025)

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

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations
by: Xu, Xiang, et al.
Published: (2025)

4D-ROLLS: 4D Radar Occupancy Learning via LiDAR Supervision
by: Liu, Ruihan, et al.
Published: (2025)

LiDAR-based 4D Occupancy Completion and Forecasting
by: Liu, Xinhao, et al.
Published: (2023)

Analyzing Infrastructure LiDAR Placement with Realistic LiDAR Simulation Library
by: Cai, Xinyu, et al.
Published: (2022)

See4D: Pose-Free 4D Generation via Auto-Regressive Video Inpainting
by: Lu, Dongyue, et al.
Published: (2025)

SAM4D: Segment Anything in Camera and LiDAR Streams
by: Xu, Jianyun, et al.
Published: (2025)

Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous Driving
by: Kong, Lingdong, et al.
Published: (2024)

SN-LiDAR: Semantic Neural Fields for Novel Space-time View LiDAR Synthesis
by: Chen, Yi, et al.
Published: (2025)

Efficient Active Training for Deep LiDAR Odometry
by: Zhou, Beibei, et al.
Published: (2025)

Is Your Driving World Model an All-Around Player?
by: Kong, Lingdong, et al.
Published: (2026)

Towards Generalized Range-View LiDAR Segmentation in Adverse Weather
by: Yang, Longyu, 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)

DSLO: Deep Sequence LiDAR Odometry Based on Inconsistent Spatio-temporal Propagation
by: Zhang, Huixin, et al.
Published: (2024)

TeFF: Tracking-enhanced Forgetting-free Few-shot 3D LiDAR Semantic Segmentation
by: Zhou, Junbao, et al.
Published: (2024)

KDD-LOAM: Jointly Learned Keypoint Detector and Descriptors Assisted LiDAR Odometry and Mapping
by: Huang, Renlang, et al.
Published: (2023)

Fast LiDAR Data Generation with Rectified Flows
by: Nakashima, Kazuto, et al.
Published: (2024)

Better Monocular 3D Detectors with LiDAR from the Past
by: You, Yurong, et al.
Published: (2024)

NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic Segmentation
by: Wang, Xuzhi, et al.
Published: (2025)