PSA-SSL: Pose and Size-aware Self-Supervised Learning on LiDAR Point Clouds
Fuente:
arXiv
Saved in:
| Main Authors: | Nisar, Barza, Waslander, Steven L. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
JDT3D: Addressing the Gaps in LiDAR-Based Tracking-by-Attention
by: Cheong, Brian, et al.
Published: (2024)
by: Cheong, Brian, et al.
Published: (2024)
Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point Clouds
by: Cai, Mu, et al.
Published: (2024)
by: Cai, Mu, et al.
Published: (2024)
NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields
by: Zhang, Junge, et al.
Published: (2023)
by: Zhang, Junge, et al.
Published: (2023)
SCATR: Mitigating New Instance Suppression in LiDAR-based Tracking-by-Attention via Second Chance Assignment and Track Query Dropout
by: Cheong, Brian, et al.
Published: (2026)
by: Cheong, Brian, et al.
Published: (2026)
TULIP: Transformer for Upsampling of LiDAR Point Clouds
by: Yang, Bin, et al.
Published: (2023)
by: Yang, Bin, et al.
Published: (2023)
Learning Human-Object Interaction for 3D Human Pose Estimation from LiDAR Point Clouds
by: Jung, Daniel Sungho, et al.
Published: (2026)
by: Jung, Daniel Sungho, et al.
Published: (2026)
Multi-Scale Neighborhood Occupancy Masked Autoencoder for Self-Supervised Learning in LiDAR Point Clouds
by: Abdelsamad, Mohamed, et al.
Published: (2025)
by: Abdelsamad, Mohamed, et al.
Published: (2025)
Text2LiDAR: Text-guided LiDAR Point Cloud Generation via Equirectangular Transformer
by: Wu, Yang, et al.
Published: (2024)
by: Wu, Yang, et al.
Published: (2024)
3D Human Pose and Shape Estimation from LiDAR Point Clouds: A Review
by: Galaaoui, Salma, et al.
Published: (2025)
by: Galaaoui, Salma, et al.
Published: (2025)
Unlocking Generalization Power in LiDAR Point Cloud Registration
by: Zeng, Zhenxuan, et al.
Published: (2025)
by: Zeng, Zhenxuan, et al.
Published: (2025)
Physics-Aware Diffusion for LiDAR Point Cloud Densification
by: Zhang, Zeping, et al.
Published: (2026)
by: Zhang, Zeping, et al.
Published: (2026)
LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object Detection
by: Fang, Jin, et al.
Published: (2023)
by: Fang, Jin, et al.
Published: (2023)
LiDARDraft: Generating LiDAR Point Cloud from Versatile Inputs
by: Wei, Haiyun, et al.
Published: (2025)
by: Wei, Haiyun, et al.
Published: (2025)
Small Object Tracking in LiDAR Point Cloud: Learning the Target-awareness Prototype and Fine-grained Search Region
by: Tian, Shengjing, et al.
Published: (2024)
by: Tian, Shengjing, et al.
Published: (2024)
Real-time Neural Rendering of LiDAR Point Clouds
by: Vanherck, Joni, et al.
Published: (2025)
by: Vanherck, Joni, et al.
Published: (2025)
Automated Road Extraction and Centreline Fitting in LiDAR Point Clouds
by: Wang, Xinyu, et al.
Published: (2025)
by: Wang, Xinyu, et al.
Published: (2025)
Ghosts in the Point Clouds: De-glaring LiDAR in the Transient Domain
by: Gump, Avery, et al.
Published: (2026)
by: Gump, Avery, et al.
Published: (2026)
Towards Practical Lossless Neural Compression for LiDAR Point Clouds
by: Yu, Pengpeng, et al.
Published: (2026)
by: Yu, Pengpeng, et al.
Published: (2026)
Towards Practical Human Motion Prediction with LiDAR Point Clouds
by: Han, Xiao, et al.
Published: (2024)
by: Han, Xiao, et al.
Published: (2024)
PACE: Post-Causal Entropy Modeling for Learned LiDAR Point Cloud Compression
by: Zhu, Jiahao, et al.
Published: (2026)
by: Zhu, Jiahao, et al.
Published: (2026)
GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting
by: Jiang, Junzhe, et al.
Published: (2025)
by: Jiang, Junzhe, et al.
Published: (2025)
Efficient Point Transformer with Dynamic Token Aggregating for LiDAR Point Cloud Processing
by: Lu, Dening, et al.
Published: (2024)
by: Lu, Dening, et al.
Published: (2024)
Point2Building: Reconstructing Buildings from Airborne LiDAR Point Clouds
by: Liu, Yujia, et al.
Published: (2024)
by: Liu, Yujia, et al.
Published: (2024)
Ranking-aware Continual Learning for LiDAR Place Recognition
by: Wang, Xufei, et al.
Published: (2025)
by: Wang, Xufei, et al.
Published: (2025)
Range Image-Based Implicit Neural Compression for LiDAR Point Clouds
by: Kuwabara, Akihiro, et al.
Published: (2025)
by: Kuwabara, Akihiro, et al.
Published: (2025)
Contextual Range-View Projection for 3D LiDAR Point Clouds
by: Mousavi, Seyedali, et al.
Published: (2026)
by: Mousavi, Seyedali, et al.
Published: (2026)
Equivariant Spatio-Temporal Self-Supervision for LiDAR Object Detection
by: Hegde, Deepti, et al.
Published: (2024)
by: Hegde, Deepti, et al.
Published: (2024)
SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving
by: Cortinhal, Tiago, et al.
Published: (2020)
by: Cortinhal, Tiago, et al.
Published: (2020)
SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Clouds
by: Wang, Yanbo, et al.
Published: (2024)
by: Wang, Yanbo, et al.
Published: (2024)
Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation
by: Yang, Bin, et al.
Published: (2026)
by: Yang, Bin, et al.
Published: (2026)
TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation
by: Liu, Jiuming, et al.
Published: (2025)
by: Liu, Jiuming, et al.
Published: (2025)
Self-supervised Learning of LiDAR 3D Point Clouds via 2D-3D Neural Calibration
by: Zhang, Yifan, et al.
Published: (2024)
by: Zhang, Yifan, et al.
Published: (2024)
SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds
by: Chen, Chuang, et al.
Published: (2025)
by: Chen, Chuang, et al.
Published: (2025)
POD: Predictive Object Detection with Single-Frame FMCW LiDAR Point Cloud
by: Shi, Yining, et al.
Published: (2025)
by: Shi, Yining, et al.
Published: (2025)
Label-Efficient Semantic Segmentation of LiDAR Point Clouds in Adverse Weather Conditions
by: Piroli, Aldi, et al.
Published: (2024)
by: Piroli, Aldi, et al.
Published: (2024)
Fast Attention-Based Simplification of LiDAR Point Clouds for Object Detection and Classification
by: Rozsa, Z., et al.
Published: (2026)
by: Rozsa, Z., et al.
Published: (2026)
3D Learnable Supertoken Transformer for LiDAR Point Cloud Scene Segmentation
by: Lu, Dening, et al.
Published: (2024)
by: Lu, Dening, et al.
Published: (2024)
Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation
by: Zheng, Yu, et al.
Published: (2023)
by: Zheng, Yu, et al.
Published: (2023)
RaLiFlow: Scene Flow Estimation with 4D Radar and LiDAR Point Clouds
by: Fu, Jingyun, et al.
Published: (2025)
by: Fu, Jingyun, et al.
Published: (2025)
OmniColor: A Global Camera Pose Optimization Approach of LiDAR-360Camera Fusion for Colorizing Point Clouds
by: Liu, Bonan, et al.
Published: (2024)
by: Liu, Bonan, et al.
Published: (2024)
Similar Items
-
JDT3D: Addressing the Gaps in LiDAR-Based Tracking-by-Attention
by: Cheong, Brian, et al.
Published: (2024) -
Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point Clouds
by: Cai, Mu, et al.
Published: (2024) -
NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields
by: Zhang, Junge, et al.
Published: (2023) -
SCATR: Mitigating New Instance Suppression in LiDAR-based Tracking-by-Attention via Second Chance Assignment and Track Query Dropout
by: Cheong, Brian, et al.
Published: (2026) -
TULIP: Transformer for Upsampling of LiDAR Point Clouds
by: Yang, Bin, et al.
Published: (2023)