Ming C. Wu — accepted AI-conference papers

2025

TrajSSL: Trajectory-Enhanced Semi-Supervised 3D Object Detection

Philip L. Jacobson, Yichen Xie, Mingyu Ding, Chenfeng Xu, Masayoshi Tomizuka, Wei Zhan +1

ICRA 2025

Semi-supervised 3D object detection is a common strategy employed to circumvent the challenge of manually labeling large-scale autonomous driving perception datasets. Pseudo-labeling approaches to semi-supervised learning adopt a teacher-student framework in which machine-generated pseudo-labels on

Cited by 0 Source ↗Scholar ↗

2023

Center Feature Fusion: Selective Multi-Sensor Fusion of Center-based Objects

Philip Jacobson, Yiyang Zhou, Wei Zhan, Masayoshi Tomizuka, Ming C. Wu

ICRA 2023poster

Leveraging multi-modal fusion, especially between camera and LiDAR, has become essential for building accurate and robust 3D object detection systems for autonomous vehicles. Until recently, point decorating approaches, in which point clouds are augmented with camera features, have been the dominant…

Cited by 10 Source ↗Scholar ↗