16 citations · 20 across the 4 of their papers we have counts for
5 papers
Spatial-aware Vision Language Model for Autonomous Driving
Weijie Wei, Zhipeng Luo, Ling Feng +1
While Vision-Language Models (VLMs) show significant promise for end-to-end autonomous driving by leveraging the common sense embedded in language models, their reliance on 2D imag…
nuScenes Revisited: Progress and Challenges in Autonomous Driving
Whye Kit Fong, Venice Erin Liong, Kok Seang Tan +1
Autonomous Vehicles (AV) and Advanced Driver Assistance Systems (ADAS) have been revolutionized by Deep Learning. As a data-driven approach, Deep Learning relies on vast amounts of…
ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation
Lingdong Kong, Niamul Quader, Venice Erin Liong
Transferring knowledge learned from the labeled source domain to the raw target domain for unsupervised domain adaptation (UDA) is essential to the scalable deployment of autonomou…
AMVNet: Assertion-based Multi-View Fusion Network for LiDAR Semantic Segmentation
Venice Erin Liong, Thi Ngoc Tho Nguyen, Sergi Widjaja +2
In this paper, we present an Assertion-based Multi-View Fusion network (AMVNet) for LiDAR semantic segmentation which aggregates the semantic features of individual projection-base…
nuScenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H. Lang +7
Robust detection and tracking of objects is crucial for the deployment of autonomous vehicle technology. Image based benchmark datasets have driven development in computer vision t…