2 citations · 2 across the 4 of their papers we have counts for
5 papers · 1 filter
DLWM: Dual Latent World Models enable Holistic Gaussian-centric Pre-training in Autonomous Driving
Yiyao Zhu, Ying Xue, Haiming Zhang +8
Vision-based autonomous driving has gained much attention due to its low costs and excellent performance. Compared with dense BEV (Bird's Eye View) or sparse query models, Gaussian…
Group Inertial Poser: Multi-Person Pose and Global Translation from Sparse Inertial Sensors and Ultra-Wideband Ranging
Ying Xue, Jiaxi Jiang, Rayan Armani +3
Tracking human full-body motion using sparse wearable inertial measurement units (IMUs) overcomes the limitations of occlusion and instrumentation of the environment inherent in vi…
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…
D-World: An Efficient World Model through Decoupled Dynamic Flow
Haiming Zhang, Xu Yan, Ying Xue +4
This technical report summarizes the second-place solution for the Predictive World Model Challenge held at the CVPR-2024 Workshop on Foundation Models for Autonomous Systems. We i…
X4D-SceneFormer: Enhanced Scene Understanding on 4D Point Cloud Videos through Cross-modal Knowledge Transfer
Linglin Jing, Ying Xue, Xu Yan +7
The field of 4D point cloud understanding is rapidly developing with the goal of analyzing dynamic 3D point cloud sequences. However, it remains a challenging task due to the spars…