13 citations · 63 across the 24 of their papers we have counts for
9 papers · 1 filter
AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection
Zongdai Liu, Dingfu Zhou, Feixiang Lu +2
Existing deep learning-based approaches for monocular 3D object detection in autonomous driving often model the object as a rotated 3D cuboid while the object's geometric shape has…
Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation
Lina Liu, Xibin Song, Mengmeng Wang +2
Remarkable results have been achieved by DCNN based self-supervised depth estimation approaches. However, most of these approaches can only handle either day-time or night-time ima…
Excavation Learning for Rigid Objects in Clutter
Qingkai Lu, Liangjun Zhang
Autonomous excavation for hard or compact materials, especially irregular rigid objects, is challenging due to high variance of geometric and physical properties of objects, and la…
FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detection
Shaoqing Xu, Dingfu Zhou, Jin Fang +3
Accurate detection of obstacles in 3D is an essential task for autonomous driving and intelligent transportation. In this work, we propose a general multimodal fusion framework Fus…
Large Scale Autonomous Driving Scenarios Clustering with Self-supervised Feature Extraction
Jinxin Zhao, Jin Fang, Zhixian Ye +1
The clustering of autonomous driving scenario data can substantially benefit the autonomous driving validation and simulation systems by improving the simulation tests' completenes…
Robust 2D/3D Vehicle Parsing in CVIS
Hui Miao, Feixiang Lu, Zongdai Liu +3
We present a novel approach to robustly detect and perceive vehicles in different camera views as part of a cooperative vehicle-infrastructure system (CVIS). Our formulation is des…