45 citations · 89 across the 8 of their papers we have counts for
4 papers · 1 filter
VADet: Multi-frame LiDAR 3D Object Detection using Variable Aggregation
Chengjie Huang, Vahdat Abdelzad, Sean Sedwards +1
Input aggregation is a simple technique used by state-of-the-art LiDAR 3D object detectors to improve detection. However, increasing aggregation is known to have diminishing return…
SOAP: Cross-sensor Domain Adaptation for 3D Object Detection Using Stationary Object Aggregation Pseudo-labelling
Chengjie Huang, Vahdat Abdelzad, Sean Sedwards +1
We consider the problem of cross-sensor domain adaptation in the context of LiDAR-based 3D object detection and propose Stationary Object Aggregation Pseudo-labelling (SOAP) to gen…
XC: Exploring Quantitative Use Cases for Explanations in 3D Object Detection
Sunsheng Gu, Vahdat Abdelzad, Krzysztof Czarnecki
Explainable AI (XAI) methods are frequently applied to obtain qualitative insights about deep models' predictions. However, such insights need to be interpreted by a human observer…
Out-of-Distribution Detection for LiDAR-based 3D Object Detection
Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad +5
3D object detection is an essential part of automated driving, and deep neural networks (DNNs) have achieved state-of-the-art performance for this task. However, deep models are no…