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Shiquan Zhang

3 accepted papers

2023

BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection

ICLR 2023poster

3D object detection from multiple image views is a fundamental and challenging task for visual scene understanding. Owing to its low cost and high efficiency, multi-view 3D object detection has demonstrated promising application prospects. However, accurately detecting objects through perspective vi…

2022

AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection

IJCAI 2022poster

Object detection through either RGB images or the LiDAR point clouds has been extensively explored in autonomous driving. However, it remains challenging to make these two data sources complementary and beneficial to each other. In this paper, we propose AutoAlign, an automatic feature fusion strat…

Cited by 140SourcePDFScholar
2022

Deformable Feature Aggregation for Dynamic Multi-modal 3D Object Detection

ECCV 2022poster

"Point clouds and RGB images are two general perceptional sources in autonomous driving. The former can provide accurate localization of objects, and the latter is denser and richer in semantic information. Recently, AutoAlign presents a learnable paradigm in combining these two modalities for 3D ob…