Qingyong Hu

16

Papers

4

Total Citations

Papers (16)

ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression

Learning Coupled Dictionaries from Unpaired Data for Image Super-Resolution

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

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

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

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

3DAC: Learning Attribute Compression for Point Clouds

Backdoor Defense via Deconfounded Representation Learning

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

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

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

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

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

Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

Hierarchical Graph Transformer with Adaptive Node Sampling