40 citations · 48 across the 17 of their papers we have counts for
8 papers · 1 filter
SMGDiff: Soccer Motion Generation using diffusion probabilistic models
Hongdi Yang, Chengyang Li, Zhenxuan Wu +5
Soccer is a globally renowned sport with significant applications in video games and VR/AR. However, generating realistic soccer motions remains challenging due to the intricate in…
A Unified Diffusion Framework for Scene-aware Human Motion Estimation from Sparse Signals
Jiangnan Tang, Jingya Wang, Kaiyang Ji +3
Estimating full-body human motion via sparse tracking signals from head-mounted displays and hand controllers in 3D scenes is crucial to applications in AR/VR. One of the biggest c…
HOI-M3:Capture Multiple Humans and Objects Interaction within Contextual Environment
Juze Zhang, Jingyan Zhang, Zining Song +6
Humans naturally interact with both others and the surrounding multiple objects, engaging in various social activities. However, recent advances in modeling human-object interactio…
LetsGo: Large-Scale Garage Modeling and Rendering via LiDAR-Assisted Gaussian Primitives
Jiadi Cui, Junming Cao, Fuqiang Zhao +7
Large garages are ubiquitous yet intricate scenes that present unique challenges due to their monotonous colors, repetitive patterns, reflective surfaces, and transparent vehicle g…
THOR: Text to Human-Object Interaction Diffusion via Relation Intervention
Qianyang Wu, Ye Shi, Xiaoshui Huang +3
This paper addresses new methodologies to deal with the challenging task of generating dynamic Human-Object Interactions from textual descriptions (Text2HOI). While most existing w…
Gaze-guided Hand-Object Interaction Synthesis: Dataset and Method
Jie Tian, Ran Ji, Lingxiao Yang +6
Gaze plays a crucial role in revealing human attention and intention, particularly in hand-object interaction scenarios, where it guides and synchronizes complex tasks that require…
LiveHPS: LiDAR-based Scene-level Human Pose and Shape Estimation in Free Environment
Yiming Ren, Xiao Han, Chengfeng Zhao +4
For human-centric large-scale scenes, fine-grained modeling for 3D human global pose and shape is significant for scene understanding and can benefit many real-world applications.…
Capturing the Unseen: Vision-Free Facial Motion Capture Using Inertial Measurement Units
Youjia Wang, Yiwen Wu, Hengan Zhou +9
We present Capturing the Unseen (CAPUS), a novel facial motion capture (MoCap) technique that operates without visual signals. CAPUS leverages miniaturized Inertial Measurement Uni…