69 citations · 215 across the 26 of their papers we have counts for
6 papers · 1 filter
ARGUS: Visualization of AI-Assisted Task Guidance in AR
Sonia Castelo, Joao Rulff, Erin McGowan +15
The concept of augmented reality (AR) assistants has captured the human imagination for decades, becoming a staple of modern science fiction. To pursue this goal, it is necessary t…
MapTRv2: An End-to-End Framework for Online Vectorized HD Map Construction
Bencheng Liao, Shaoyu Chen, Yunchi Zhang +5
High-definition (HD) map provides abundant and precise static environmental information of the driving scene, serving as a fundamental and indispensable component for planning in a…
TinyDet: Accurate Small Object Detection in Lightweight Generic Detectors
Shaoyu Chen, Tianheng Cheng, Jiemin Fang +4
Small object detection requires the detection head to scan a large number of positions on image feature maps, which is extremely hard for computation- and energy-efficient lightwei…
VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene
Shaoyu Chen, Yunchi Zhang, Bencheng Liao +7
High-definition (HD) map serves as the essential infrastructure of autonomous driving. In this work, we build up a systematic vectorized map annotation framework (termed VMA) for e…
VAD: Vectorized Scene Representation for Efficient Autonomous Driving
Bo Jiang, Shaoyu Chen, Qing Xu +7
Autonomous driving requires a comprehensive understanding of the surrounding environment for reliable trajectory planning. Previous works rely on dense rasterized scene representat…
Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Construction
Bencheng Liao, Shaoyu Chen, Bo Jiang +5
Online lane graph construction is a promising but challenging task in autonomous driving. Previous methods usually model the lane graph at the pixel or piece level, and recover the…