Pengcheng Zhu - 朱鹏程

I am a M.Sc. student at Northeastern University, Shenyang, China, supervised by Prof. Yaoming Zhuang. My current research interests focus on AI-based 3D computer vision, Visual SLAM, Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS). Before this, I won 6 national awards in academic competitions during my undergraduate studies and was guaranteed a place in graduate school with distinction. I am the outstanding graduate of Henan Province in 2022 and Liaoning Province in 2025. I was also an algorithm intern at Didichuxing, focusing on Autonomous driving.

Email  /  GitHub  /  Bilibili  /  YouTube

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Publications

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BEV-PolyNet: BEV-Based Polygonal End to End Parking Slot Detection Framework
Zhenjie Duan, Yaoming Zhuang*, Yifan Chao, Pengcheng Zhu, Li Li, Chengdong Wu.
[RA-L 2025]  /  Paper

Accurate parking slot detection is vital for autonomous parking and intelligent driving. However, existing methods relying on AVM images suffer from distortion, occlusion, and fragmented corner-point regression. To overcome these issues, we propose BEV-PolyNet, an end-to-end framework that generates BEV features from surround-view images, introduces polygonal modeling to capture complete slot structures, and enhances convergence via query initialization with image features and location priors. Experiments on the PS2.0 and LPD datasets demonstrate BEV-PolyNet's superior accuracy and robustness.

MGS-SLAM: Monocular Sparse Tracking and Gaussian Mapping with Depth Smooth Regularization
Pengcheng Zhu, Yaoming Zhuang*, Baoquan Chen, Li Li, Chengdong Wu, Zhanlin Liu.
[RA-L 2024]  /  Paper  /  Code  /  Bilibili  /  YouTube

The work uniquely integrates advanced sparse visual odometry with a dense Gaussian Splatting scene representation for the first time, thereby eliminating the dependency on depth maps typical of Gaussian Splatting-based SLAM systems and enhancing tracking robustness. We have evaluated our system across various synthetic and real-world datasets. The accuracy of our pose estimation surpasses existing methods and achieves state-of-the-art performance. Additionally, it outperforms previous monocular methods in terms of novel view synthesis fidelity.

Awards

China Robotics and Artificial Intelligence Competition National First Prize in Autonomous Driving, 2019
China Robotics and Artificial Intelligence Competition National First Prize in Deep Learning, 2019
China Robotics Competition National Third Prize, 2019
Nation College Student Intelligent Car Competition National Second Prize, 2020
Nation College Student Engineering Training Competition National Second Prize, 2021
China Robotics and Artificial Intelligence Competition National Second Prize in Autonomous Driving, 2021

Academic Services

Journal Reviewer: RA-L
Conference Reviewer: ICRA 2025
Conference Reviewer: IEEE VR 2025

Contact

Pengcheng Zhu
Northeastern University, Shenyang
China

Last update: 22 Oct 2025