Qingyong Hu

Orcid: 0000-0003-0337-9207

According to our database¹, Qingyong Hu authored at least 48 papers between 2016 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Bibliography

2024

Rethinking Dual-Stream Super-Resolution Semantic Learning in Medical Image Segmentation.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., January, 2024

Divide and Conquer: Improving Multi-Camera 3D Perception With 2D Semantic-Depth Priors and Input-Dependent Queries.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2024

GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing.

[BibT_eX]

[DOI]

CoRR, 2024

FedGT: Federated Node Classification with Scalable Graph Transformer.

[BibT_eX]

[DOI]

CoRR, 2024

2023

SF-Adapter: Computational-Efficient Source-Free Domain Adaptation for Human Activity Recognition.

[BibT_eX]

[DOI]

Hua Kang

Qingyong Hu

Qian Zhang

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., December, 2023

RoReg: Pairwise Point Cloud Registration With Oriented Descriptors and Local Rotations.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

You Only Train Once: Learning General and Distinctive 3D Local Descriptors.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

CenterTube: Tracking Multiple 3D Objects With 4D Tubelets in Dynamic Point Clouds.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2023

DeepPCT: Single Object Tracking in Dynamic Point Cloud Sequences.

[BibT_eX]

[DOI]

IEEE Trans. Instrum. Meas., 2023

V2P-SSD: Single-Stage 3-D Object Detection With Voxel-to-Point Transformation.

[BibT_eX]

[DOI]

IEEE Geosci. Remote. Sens. Lett., 2023

PVP: Pre-trained Visual Parameter-Efficient Tuning.

[BibT_eX]

[DOI]

CoRR, 2023

Small but Mighty: Enhancing 3D Point Clouds Semantic Segmentation with U-Next Framework.

[BibT_eX]

[DOI]

CoRR, 2023

CSI-StripeFormer: Exploiting Stripe Features for CSI Compression in Massive MIMO System.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2023, 2023

VPPT: Visual Pre-Trained Prompt Tuning Framework for Few-Shot Image Classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

Backdoor Defense via Deconfounded Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

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

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2022

Learning Semantic Segmentation of Large-Scale Point Clouds With Random Sampling.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Continuous Mapping Convolution for Large-Scale Point Clouds Semantic Segmentation.

[BibT_eX]

[DOI]

IEEE Geosci. Remote. Sens. Lett., 2022

EarSpiro: Earphone-based Spirometry for Lung Function Assessment.

[BibT_eX]

[DOI]

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022

SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Clouds.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2022

4DAC: Learning Attribute Compression for Dynamic Point Clouds.

[BibT_eX]

[DOI]

CoRR, 2022

STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset.

[BibT_eX]

[DOI]

CoRR, 2022

Box2Seg: Learning Semantics of 3D Point Clouds with Box-Level Supervision.

[BibT_eX]

[DOI]

CoRR, 2022

Hierarchical Graph Transformer with Adaptive Node Sampling.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The First Challenge on Moving Object Detection and Tracking in Satellite Videos: Methods and Results.

[BibT_eX]

[DOI]

Proceedings of the 26th International Conference on Pattern Recognition, 2022

DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

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

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

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

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static Models by Fitting Feature-level Space-time Surfaces.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

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

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

3DAC: Learning Attribute Compression for Point Clouds.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset.

[BibT_eX]

[DOI]

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Deep Learning for 3D Point Clouds: A Survey.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2021

SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds with 1000x Fewer Labels.

[BibT_eX]

[DOI]

CoRR, 2021

Cgan-Net: Class-Guided Asymmetric Non-Local Network for Real-Time Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

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

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

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

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Robust Long-Term Tracking via Instance-Specific Proposals.

[BibT_eX]

[DOI]

IEEE Trans. Instrum. Meas., 2020

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

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNs.

[BibT_eX]

[DOI]

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

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

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Semi-Online Multiple Object Tracking Using Graphical Tracklet Association.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2018

Long-term Object Tracking with Instance Specific Proposals.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017

Object Tracking Using Multiple Features and Adaptive Model Updating.

[BibT_eX]

[DOI]

IEEE Trans. Instrum. Meas., 2017

Fast Correlation Tracking Using Low-Dimensional Scale Filter and Local Search Strategy.

[BibT_eX]

[DOI]

IEEE Access, 2017

Correlation Filter Tracking: Beyond an Open-loop System.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference 2017, 2017

2016

Robust and Real-Time Object Tracking Using Scale-Adaptive Correlation Filters.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Conference on Digital Image Computing: Techniques and Applications, 2016

Qingyong Hu

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