Chaoqun Wang

Affiliations:
  • Chinese University of Hong Kong - Shenzhen (CUHK-SZ), School of Science and Engineering, Shenzhen, China


According to our database1, Chaoqun Wang authored at least 13 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Boosting 3D Object Detection via Self-Distilling Introspective Data.
IEEE Trans. Intell. Transp. Syst., May, 2025

Unlock the Power of Unlabeled Data in Language Driving Model.
Proceedings of the IEEE International Conference on Robotics and Automation, 2025

Semantic-Supervised Spatial-Temporal Fusion for LiDAR-Based 3D Object Detection.
Proceedings of the IEEE International Conference on Robotics and Automation, 2025

2024
Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Label Attentive Distillation for GNN-Based Graph Classification.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Learning cross-modal interaction for RGB-T tracking.
Sci. China Inf. Sci., January, 2023

Visual Micro-Pattern Propagation.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Toward Unpaired Multi-modal Medical Image Segmentation via Learning Structured Semantic Consistency.
Proceedings of the Medical Imaging with Deep Learning, 2023

SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Semantic Human Parsing via Scalable Semantic Transfer Over Multiple Label Domains.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Toward Unpaired Multi-modal Medical Image Segmentation via Learning Structured Semantic Consistency.
CoRR, 2022

2020
Pattern-Structure Diffusion for Multi-Task Learning.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Cross-Modal Pattern-Propagation for RGB-T Tracking.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020


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