FLaTEC: Frequency-Disentangled Latent Triplanes for Efficient Compression of LiDAR Point Clouds
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Xiaoge, Wu, Zijie, Feng, Mingtao, Geng, Zichen, Nasim, Mehwish, Anwar, Saeed, Mian, Ajmal |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DiffCom: Decoupled Sparse Priors Guided Diffusion Compression for Point Clouds
by: Zhang, Xiaoge, et al.
Published: (2024)
by: Zhang, Xiaoge, et al.
Published: (2024)
Automated Road Extraction and Centreline Fitting in LiDAR Point Clouds
by: Wang, Xinyu, et al.
Published: (2025)
by: Wang, Xinyu, et al.
Published: (2025)
Multistream Network for LiDAR and Camera-based 3D Object Detection in Outdoor Scenes
by: Ibrahim, Muhammad, et al.
Published: (2025)
by: Ibrahim, Muhammad, et al.
Published: (2025)
Sparse Points to Dense Clouds: Enhancing 3D Detection with Limited LiDAR Data
by: Kumar, Aakash, et al.
Published: (2024)
by: Kumar, Aakash, et al.
Published: (2024)
Geo-Registration of Terrestrial LiDAR Point Clouds with Satellite Images without GNSS
by: Wang, Xinyu, et al.
Published: (2025)
by: Wang, Xinyu, et al.
Published: (2025)
PointDiffuse: A Dual-Conditional Diffusion Model for Enhanced Point Cloud Semantic Segmentation
by: He, Yong, et al.
Published: (2025)
by: He, Yong, et al.
Published: (2025)
Class-Partitioned VQ-VAE and Latent Flow Matching for Point Cloud Scene Generation
by: Edirimuni, Dasith de Silva, et al.
Published: (2026)
by: Edirimuni, Dasith de Silva, et al.
Published: (2026)
3D Object Detection from Point Cloud via Voting Step Diffusion
by: Hou, Haoran, et al.
Published: (2024)
by: Hou, Haoran, et al.
Published: (2024)
LiZIP: An Auto-Regressive Compression Framework for LiDAR Point Clouds
by: Shibu, Aditya, et al.
Published: (2026)
by: Shibu, Aditya, et al.
Published: (2026)
On the Impact of LiDAR Point Cloud Compression on Remote Semantic Segmentation
by: Fernandes, Tiago de S., et al.
Published: (2025)
by: Fernandes, Tiago de S., et al.
Published: (2025)
Towards Practical Lossless Neural Compression for LiDAR Point Clouds
by: Yu, Pengpeng, et al.
Published: (2026)
by: Yu, Pengpeng, et al.
Published: (2026)
Mantis: Mamba-native Tuning is Efficient for 3D Point Cloud Foundation Models
by: Guo, Zihao, et al.
Published: (2026)
by: Guo, Zihao, et al.
Published: (2026)
Auto-Regressive Diffusion for Generating 3D Human-Object Interactions
by: Geng, Zichen, et al.
Published: (2025)
by: Geng, Zichen, et al.
Published: (2025)
LPCM: Learning-based Predictive Coding for LiDAR Point Cloud Compression
by: Sun, Chang, et al.
Published: (2025)
by: Sun, Chang, 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)
Multiview Point Cloud Registration Based on Minimum Potential Energy for Free-Form Blade Measurement
by: Wu, Zijie, et al.
Published: (2025)
by: Wu, Zijie, et al.
Published: (2025)
LiDAR-Forest Dataset: LiDAR Point Cloud Simulation Dataset for Forestry Application
by: Lu, Yawen, et al.
Published: (2024)
by: Lu, Yawen, et al.
Published: (2024)
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)
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)
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)
Real-Time LiDAR Point Cloud Compression and Transmission for Resource-constrained Robots
by: Cao, Yuhao, et al.
Published: (2025)
by: Cao, Yuhao, et al.
Published: (2025)
RENO: Real-Time Neural Compression for 3D LiDAR Point Clouds
by: You, Kang, et al.
Published: (2025)
by: You, Kang, et al.
Published: (2025)
Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression
by: Wei, Hao, et al.
Published: (2026)
by: Wei, Hao, 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)
LiLa-Net: Lightweight Latent LiDAR Autoencoder for 3D Point Cloud Reconstruction
by: Resino, Mario, et al.
Published: (2025)
by: Resino, Mario, 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)
Learning Coherent Matrixized Representation in Latent Space for Volumetric 4D Generation
by: Yang, Qitong, et al.
Published: (2024)
by: Yang, Qitong, et al.
Published: (2024)
Disentangled Hierarchical VAE for 3D Human-Human Interaction Generation
by: Geng, Zichen, et al.
Published: (2026)
by: Geng, Zichen, et al.
Published: (2026)
Text2LiDAR: Text-guided LiDAR Point Cloud Generation via Equirectangular Transformer
by: Wu, Yang, et al.
Published: (2024)
by: Wu, Yang, et al.
Published: (2024)
Efficient Dynamic LiDAR Odometry for Mobile Robots with Structured Point Clouds
by: Lichtenfeld, Jonathan, et al.
Published: (2024)
by: Lichtenfeld, Jonathan, et al.
Published: (2024)
Diffusion Masked Pretraining for Dynamic Point Cloud
by: Zhang, Zhuoyue, et al.
Published: (2026)
by: Zhang, Zhuoyue, 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)
Real-time Neural Rendering of LiDAR Point Clouds
by: Vanherck, Joni, et al.
Published: (2025)
by: Vanherck, Joni, et al.
Published: (2025)
SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds
by: Chen, Chuang, et al.
Published: (2025)
by: Chen, Chuang, 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)
LiDAR-based 3D Change Detection at City Scale
by: Albagami, Hezam, et al.
Published: (2025)
by: Albagami, Hezam, et al.
Published: (2025)
Accurate Calibration and Robust LiDAR-Inertial Odometry for Spinning Actuated LiDAR Systems
by: Chen, Zijie, et al.
Published: (2026)
by: Chen, Zijie, et al.
Published: (2026)
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)
Similar Items
-
DiffCom: Decoupled Sparse Priors Guided Diffusion Compression for Point Clouds
by: Zhang, Xiaoge, et al.
Published: (2024) -
Automated Road Extraction and Centreline Fitting in LiDAR Point Clouds
by: Wang, Xinyu, et al.
Published: (2025) -
Multistream Network for LiDAR and Camera-based 3D Object Detection in Outdoor Scenes
by: Ibrahim, Muhammad, et al.
Published: (2025) -
Sparse Points to Dense Clouds: Enhancing 3D Detection with Limited LiDAR Data
by: Kumar, Aakash, et al.
Published: (2024) -
Geo-Registration of Terrestrial LiDAR Point Clouds with Satellite Images without GNSS
by: Wang, Xinyu, et al.
Published: (2025)