Huawei Sun

Orcid: 0009-0000-1393-1822

According to our database1, Huawei Sun authored at least 14 papers between 2022 and 2025.

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

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2025
CaRaFFusion: Improving 2D Semantic Segmentation With Camera-Radar Point Cloud Fusion and Zero-Shot Image Inpainting.
IEEE Robotics Autom. Lett., July, 2025

ELMAR: Enhancing LiDAR Detection with 4D Radar Motion Awareness and Cross-modal Uncertainty.
CoRR, June, 2025

4D mmWave Radar in Adverse Environments for Autonomous Driving: A Survey.
CoRR, March, 2025

Exploiting Benford's Law for Weight Regularization of Deep Neural Networks.
Trans. Mach. Learn. Res., 2025

GET-UP: GEomeTric-aware Depth Estimation with Radar Points UPsampling.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

LiRCDepth: Lightweight Radar-Camera Depth Estimation via Knowledge Distillation and Uncertainty Guidance.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

MutualForce: Mutual-Aware Enhancement for 4D Radar-LiDAR 3D Object Detection.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024
BHPVAS: visual analysis system for pruning attention heads in BERT model.
J. Vis., August, 2024

Enhanced Radar Perception via Multi-Task Learning: Towards Refined Data for Sensor Fusion Applications.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

CaFNet: A Confidence-Driven Framework for Radar Camera Depth Estimation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

MUFASA: Multi-view Fusion and Adaptation Network with Spatial Awareness for Radar Object Detection.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

2023
Multi-Task Cross-Modality Attention-Fusion for 2D Object Detection.
Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023

2022
Utilizing Explainable AI for improving the Performance of Neural Networks.
Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Label-Aware Ranked Loss for Robust People Counting Using Automotive In-Cabin Radar.
Proceedings of the IEEE International Conference on Acoustics, 2022


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