Qingyong Hu

papers

3,183

total citations

papers (15)

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

CVPR 2020arXiv

1,832

citations

SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

CVPR 2021arXiv

359

citations

Not All Points Are Equal: Learning Highly Efficient Point-Based Detectors for 3D LiDAR Point Clouds

CVPR 2022arXiv

336

citations

Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges

CVPR 2021arXiv

197

citations

DevNet: Self-Supervised Monocular Depth Learning via Density Volume Construction

ECCV 2022arXiv

citations

No Pain, Big Gain: Classify Dynamic Point Cloud Sequences With Static Models by Fitting Feature-Level Space-Time Surfaces

CVPR 2022arXiv

citations

Meta-Sampler: Almost-Universal yet Task-Oriented Sampling for Point Clouds

ECCV 2022arXiv

citations

Period-LLM: Extending the Periodic Capability of Multimodal Large Language Model

CVPR 2025arXiv

citations

ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression

ICLR 2024

citations

BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud Registration

CVPR 2023

citations

Learning Coupled Dictionaries from Unpaired Data for Image Super-Resolution

CVPR 2024

citations

Qingyong Hu

papers (15)

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

SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

Not All Points Are Equal: Learning Highly Efficient Point-Based Detectors for 3D LiDAR Point Clouds

Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges

SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds

Hierarchical Graph Transformer with Adaptive Node Sampling

Backdoor Defense via Deconfounded Representation Learning

3DAC: Learning Attribute Compression for Point Clouds

DevNet: Self-Supervised Monocular Depth Learning via Density Volume Construction

No Pain, Big Gain: Classify Dynamic Point Cloud Sequences With Static Models by Fitting Feature-Level Space-Time Surfaces

Meta-Sampler: Almost-Universal yet Task-Oriented Sampling for Point Clouds

Period-LLM: Extending the Periodic Capability of Multimodal Large Language Model

ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression

BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud Registration

Learning Coupled Dictionaries from Unpaired Data for Image Super-Resolution

papers (15)

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

SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

Not All Points Are Equal: Learning Highly Efficient Point-Based Detectors for 3D LiDAR Point Clouds

Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges

SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds

Hierarchical Graph Transformer with Adaptive Node Sampling

Backdoor Defense via Deconfounded Representation Learning

3DAC: Learning Attribute Compression for Point Clouds

DevNet: Self-Supervised Monocular Depth Learning via Density Volume Construction

No Pain, Big Gain: Classify Dynamic Point Cloud Sequences With Static Models by Fitting Feature-Level Space-Time Surfaces

Meta-Sampler: Almost-Universal yet Task-Oriented Sampling for Point Clouds

Period-LLM: Extending the Periodic Capability of Multimodal Large Language Model

ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression

BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud Registration

Learning Coupled Dictionaries from Unpaired Data for Image Super-Resolution