2 citations · 5 across the 26 of their papers we have counts for
8 papers · 1 filter
An Efficient Occupancy World Model via Decoupled Dynamic Flow and Image-assisted Training
Haiming Zhang, Ying Xue, Xu Yan +6
The field of autonomous driving is experiencing a surge of interest in world models, which aim to predict potential future scenarios based on historical observations. In this paper…
HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Driving
Hongyu Zhou, Longzhong Lin, Jiabao Wang +6
In the past few decades, autonomous driving algorithms have made significant progress in perception, planning, and control. However, evaluating individual components does not fully…
VisionPAD: A Vision-Centric Pre-training Paradigm for Autonomous Driving
Haiming Zhang, Wending Zhou, Yiyao Zhu +7
This paper introduces VisionPAD, a novel self-supervised pre-training paradigm designed for vision-centric algorithms in autonomous driving. In contrast to previous approaches that…
3DArticCyclists: Generating Synthetic Articulated 8D Pose-Controllable Cyclist Data for Computer Vision Applications
Eduardo R. Corral-Soto, Yang Liu, Tongtong Cao +2
In Autonomous Driving (AD) Perception, cyclists are considered safety-critical scene objects. Commonly used publicly-available AD datasets typically contain large amounts of car an…
AutoSplat: Constrained Gaussian Splatting for Autonomous Driving Scene Reconstruction
Mustafa Khan, Hamidreza Fazlali, Dhruv Sharma +4
Realistic scene reconstruction and view synthesis are essential for advancing autonomous driving systems by simulating safety-critical scenarios. 3D Gaussian Splatting excels in re…
Efficient Depth-Guided Urban View Synthesis
Sheng Miao, Jiaxin Huang, Dongfeng Bai +4
Recent advances in implicit scene representation enable high-fidelity street view novel view synthesis. However, existing methods optimize a neural radiance field for each scene, r…
Neural Radiance Fields with Torch Units
Bingnan Ni, Huanyu Wang, Dongfeng Bai +4
Neural Radiance Fields (NeRF) give rise to learning-based 3D reconstruction methods widely used in industrial applications. Although prevalent methods achieve considerable improvem…
HUGS: Holistic Urban 3D Scene Understanding via Gaussian Splatting
Hongyu Zhou, Jiahao Shao, Lu Xu +6
Holistic understanding of urban scenes based on RGB images is a challenging yet important problem. It encompasses understanding both the geometry and appearance to enable novel vie…