collaborators

5 papers

cs.CV2026

ModalPatch: A Plug-and-Play Module for Robust Multi-Modal 3D Object Detection under Modality Drop

Shuangzhi Li, Lei Ma, Xingyu Li

Multi-modal 3D object detection is pivotal for autonomous driving, integrating complementary sensors like LiDAR and cameras. However, its real-world reliability is challenged by tr…

cs.RO2026

The RoboSense Challenge: Sense Anything, Navigate Anywhere, Adapt Across Platforms

Lingdong Kong, Shaoyuan Xie, Zeying Gong +135

Autonomous systems are increasingly deployed in open and dynamic environments -- from city streets to aerial and indoor spaces -- where perception models must remain reliable under…

cs.CV2026

From Dataset to Real-world: General 3D Object Detection via Generalized Cross-domain Few-shot Learning

Shuangzhi Li, Junlong Shen, Lei Ma +1

LiDAR-based 3D object detection models often struggle to generalize to real-world environments due to limited object diversity in existing datasets. To tackle it, we introduce the…

cs.CV2024

MyriadAL: Active Few Shot Learning for Histopathology

Nico Schiavone, Jingyi Wang, Shuangzhi Li +2

Active Learning (AL) and Few Shot Learning (FSL) are two label-efficient methods which have achieved excellent results recently. However, most prior arts in both learning paradigms…

cs.CV2024

Domain Generalization of 3D Object Detection by Density-Resampling

Shuangzhi Li, Lei Ma, Xingyu Li

Point-cloud-based 3D object detection suffers from performance degradation when encountering data with novel domain gaps. To tackle it, the single-domain generalization (SDG) aims…