3 citations · 5 across the 15 of their papers we have counts for
5 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…
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…
OmniBooth: Learning Latent Control for Image Synthesis with Multi-modal Instruction
Leheng Li, Weichao Qiu, Xu Yan +6
We present OmniBooth, an image generation framework that enables spatial control with instance-level multi-modal customization. For all instances, the multimodal instruction can be…
SyntheOcc: Synthesize Geometric-Controlled Street View Images through 3D Semantic MPIs
Leheng Li, Weichao Qiu, Yingjie Cai +4
The advancement of autonomous driving is increasingly reliant on high-quality annotated datasets, especially in the task of 3D occupancy prediction, where the occupancy labels requ…
Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunities
Xu Yan, Haiming Zhang, Yingjie Cai +13
The rise of large foundation models, trained on extensive datasets, is revolutionizing the field of AI. Models such as SAM, DALL-E2, and GPT-4 showcase their adaptability by extrac…