I am pursuing Ph.D. degree in School of Mechanical Science and Engineering, Huazhong University of Science and Technology. Previously, I received my M.S. degree in School of Mechanical Science and Engineering, Huazhong University of Science and Technology (2021), and B.S. degree in Hubei University of Technology (2019).

Now, I am a visiting student in A*STAR Centre for Frontier AI Research (CFAR), Singapore, supervised by Joey Tianyi Zhou and Jiawei Du.

My current research interest is computer vision including autonomous driving, multi-modality fusion, and embodied AI.

🔥 News

2024.11: 🎉 I Won the National Scholarship for PhD Student !
2024.11: 🎉 Our work “SGIFormer: Semantic-guided and Geometric-enhanced Interleaving Transformer for 3D Instance Segmentation” has been accepted by IEEE TCSVT ! Paper
2024.10: 🎉 Our work “GEM: Boost Simple Network for Glass Surface Segmentation via Vision Foundation Models” has been accepted by IEEE TMM ! Paper
2024.10: 🎉 We got 6th place in ToothFairy2 : Semi-supervised Teeth Segmentation hold on MICCAI2024 !
2024.05: 🎉 Our work “Towards Better Unguided Depth Completion via Cross-Modality Knowledge Distillation in the Frequency Domain” has been accepted by IEEE TIV ! Paper
2024.04: 🎉 Our work “MENet: Multi-Modal Mapping Enhancement Network for 3D Object Detection in Autonomous Driving” has been accepted by IEEE TITS ! Paper

📖 Educations

2023.05 - Now, Visiting Ph.D. Student, A*STAR Centre for Frontier AI Research (CFAR).
2021.09 - Now, Ph.D. Student, School of Mechanical Science and Engineering, Huazhong University of Science and Technology.
2019.06 - 2021.06, M.Eng., School of Mechanical Science and Engineering, Huazhong University of Science and Technology.
2015.09 - 2019.06, B.Eng., School of Mechanical Engineering, Hubei University of Technology.

💻 Internships

2022.07 - 2022.09, Huawei Intelligent Automotive Solution Business Unit, Shanghai, China.

📝 Selected Publications

Towards Better Unguided Depth Completion via Cross-Modality Knowledge Distillation in the Frequency Domain

Moyun Liu, Bing Chen, Youping Chen, Jingming Xie, Lei Yao, Yang Zhang, Qin Hu, Jiawei Du, Joey Tianyi Zhou

IEEE Transactions on Intelligent Vehicles, 2024

We analyze the contribution of camera image for depth completion and propose a better unguided depth completion framework.

MENet: Multi-Modal Mapping Enhancement Network for 3D Object Detection in Autonomous Driving

Moyun Liu, Youping Chen, Jingming Xie, Yijie Zhu, Yang Zhang, Lei Yao, Zhenshan Bing, Genghang Zhuang, Kai Huang, Joey Tianyi Zhou

IEEE Transactions on Intelligent Transportation Systems, 2024

We propose a multi-modal mapping enhancement network named MENet for 3D object detection.

A Concise but High-performing Network for Image Guided Depth Completion in Autonomous Driving

Moyun Liu, Bing Chen, Youping Chen, Jingming Xie, Lei Yao, Yang Zhang, Joey Tianyi Zhou

Knowledge-Based Systems, 2024 |

We propose a fast and effective depth completion network based on the image guidance.

GEM: Boost Simple Network for Glass Surface Segmentation via Vision Foundation Models

Jing Hao*, Moyun Liu*, Jinrong Yang, Kuo Feng Hung

IEEE Transactions on Multimedia, 2024 |

The first to propose exploring to the solution of glass surface segmentation by fully harnessing the capabilities of existing VFMs.

LF-YOLO: A Lighter and Faster YOLO for Weld Defect Detection of X-ray Image

Moyun Liu, Youping Chen, Jingming Xie, Lei He, Yang Zhang

IEEE Sensors Journal, 2023 |

We propose a weld defect detection method based on convolution neural network, namely Lighter and Faster YOLO (LF-YOLO).

Adaptive fusion affinity graph with noise-free online low-rank representation for natural image segmentation

Yang Zhang, Moyun Liu, Huiming Zhang, Guodong Sun, and Jingwu He

Pattern Recognition, 2023

We propose an adaptive fusion affinity graph (AFA-graph) with noise-free low-rank representation in an online manner for natural image segmentation

A lightweight and accurate recognition framework for signs of X-ray weld images

Moyun Liu, Jingming Xie, Jing Hao, Yang Zhang, Xuzhan Chen, Youping Chen

Computers in Industry, 2022

We propose a signs recognition framework based on convolutional neural networks (CNNs) for weld images. The proposed framework firstly contains a shallow classification network for correcting the pose of images, and a narrow network for final weld information recognition.

A Unified Light Framework for Real-time Fault Detection of Freight Train Images

Yang Zhang, Moyun Liu*, Yang Yang, Yanwen Guo, Huiming Zhang

IEEE Transactions on Industrial Informatics, 2021

We propose a unified light framework to improve detection accuracy while supporting a real-time operation with a low resource requirement.

Affinity fusion graph-based framework for natural image segmentation

Yang Zhang, Moyun Liu, Jingwu He, Fei Pan, Yanwen Guo

IEEE Transactions on Multimedia, 2021 |

We propose an affinity fusion graph framework to effectively connect different graphs with highly discriminating power and nonlinearity for natural image segmentation.