1 citations · 1 across the 4 of their papers we have counts for
5 papers
FSHNet: Fully Sparse Hybrid Network for 3D Object Detection
Shuai Liu, Mingyue Cui, Boyang Li +4
Fully sparse 3D detectors have recently gained significant attention due to their efficiency in long-range detection. However, sparse 3D detectors extract features only from non-em…
GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Driving
Shuai Liu, Quanmin Liang, Zefeng Li +2
Multi-sensor fusion is crucial for improving the performance and robustness of end-to-end autonomous driving systems. Existing methods predominantly adopt either attention-based fl…
FFAM: Feature Factorization Activation Map for Explanation of 3D Detectors
Shuai Liu, Boyang Li, Zhiyu Fang +2
LiDAR-based 3D object detection has made impressive progress recently, yet most existing models are black-box, lacking interpretability. Previous explanation approaches primarily f…
NIV-SSD: Neighbor IoU-Voting Single-Stage Object Detector From Point Cloud
Shuai Liu, Di Wang, Quan Wang +1
Previous single-stage detectors typically suffer the misalignment between localization accuracy and classification confidence. To solve the misalignment problem, we introduce a nov…
DCDet: Dynamic Cross-based 3D Object Detector
Shuai Liu, Boyang Li, Zhiyu Fang +1
Recently, significant progress has been made in the research of 3D object detection. However, most prior studies have focused on the utilization of center-based or anchor-based lab…