1 citations · 1 across the 5 of their papers we have counts for
5 papers
RVLoss: Runoff Vote Loss for Self-Supervised LiDAR Scene Flow Estimation
Shiming Wang, Liangliang Nan, Julian Kooij +2
LiDAR scene flow estimates point-wise motion between two consecutive scans, referred to as the source and target. Leading self-supervised methods typically minimize the Chamfer los…
AsyncBEV: Cross-modal Flow Alignment in Asynchronous 3D Object Detection
Shiming Wang, Holger Caesar, Liangliang Nan +1
In autonomous driving, multi-modal perception tasks like 3D object detection typically rely on well-synchronized sensors, both at training and inference. However, despite the use o…
A Vehicle System for Navigating Among Vulnerable Road Users Including Remote Operation
Oscar de Groot, Alberto Bertipaglia, Hidde Boekema +21
We present a vehicle system capable of navigating safely and efficiently around Vulnerable Road Users (VRUs), such as pedestrians and cyclists. The system comprises key modules for…
VoteFlow: Enforcing Local Rigidity in Self-Supervised Scene Flow
Yancong Lin, Shiming Wang, Liangliang Nan +2
Scene flow estimation aims to recover per-point motion from two adjacent LiDAR scans. However, in real-world applications such as autonomous driving, points rarely move independent…
UniBEV: Multi-modal 3D Object Detection with Uniform BEV Encoders for Robustness against Missing Sensor Modalities
Shiming Wang, Holger Caesar, Liangliang Nan +1
Multi-sensor object detection is an active research topic in automated driving, but the robustness of such detection models against missing sensor input (modality missing), e.g., d…