3 citations · 7 across the 11 of their papers we have counts for
11 papers
HiPHI: A Large-Scale Benchmark for High-Precision Human Motion and Object-Interaction
Jiahao Ji, Ji Ma, Runhan Zhang +12
Humanoid intelligence requires learning over an extremely diverse space of whole-body motions and physically grounded interactions. However, existing embodied datasets remain funda…
OmniContact: Chaining Meta-Skills via Contact Flow for Generalizable Humanoid Loco-Manipulation
Runyi Yu, Xiaoyi Lin, Ji Ma +11
Learning long-horizon humanoid loco-manipulation poses a dual challenge: it requires not only the robust execution of meta-skills but also their seamless, closed-loop chaining equi…
EgoReAct: Egocentric Video-Driven 3D Human Reaction Generation
Libo Zhang, Zekun Li, Tianyu Li +10
Humans exhibit adaptive, context-sensitive responses to egocentric visual input. However, faithfully modeling such reactions from egocentric video remains challenging due to the du…
EgoGrasp: World-Space Hand-Object Interaction Estimation from Egocentric Videos
Hongming Fu, Wenjia Wang, Xiaozhen Qiao +5
We propose EgoGrasp, the first method to reconstruct world-space hand-object interactions (W-HOI) from dynamic egoview videos, supporting open-vocabulary objects. Accurate W-HOI re…
TokenHSI: Unified Synthesis of Physical Human-Scene Interactions through Task Tokenization
Liang Pan, Zeshi Yang, Zhiyang Dou +5
Synthesizing diverse and physically plausible Human-Scene Interactions (HSI) is pivotal for both computer animation and embodied AI. Despite encouraging progress, current methods m…
Zero-Shot Human-Object Interaction Synthesis with Multimodal Priors
Yuke Lou, Yiming Wang, Zhen Wu +4
Human-object interaction (HOI) synthesis is important for various applications, ranging from virtual reality to robotics. However, acquiring 3D HOI data is challenging due to its c…
RMD: A Simple Baseline for More General Human Motion Generation via Training-free Retrieval-Augmented Motion Diffuse
Zhouyingcheng Liao, Mingyuan Zhang, Wenjia Wang +2
While motion generation has made substantial progress, its practical application remains constrained by dataset diversity and scale, limiting its ability to handle out-of-distribut…
SIMS: Simulating Stylized Human-Scene Interactions with Retrieval-Augmented Script Generation
Wenjia Wang, Liang Pan, Zhiyang Dou +7
Simulating stylized human-scene interactions (HSI) in physical environments is a challenging yet fascinating task. Prior works emphasize long-term execution but fall short in achie…
AiOS: All-in-One-Stage Expressive Human Pose and Shape Estimation
Qingping Sun, Yanjun Wang, Ailing Zeng +8
Expressive human pose and shape estimation (a.k.a. 3D whole-body mesh recovery) involves the human body, hand, and expression estimation. Most existing methods have tackled this ta…
Diffusion Models are Efficient Data Generators for Human Mesh Recovery
Yongtao Ge, Wenjia Wang, Yongfan Chen +4
Despite remarkable progress having been made on the problem of 3D human pose and shape estimation (HPS), current state-of-the-art methods rely heavily on either confined indoor moc…
EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion Generation
Wenyang Zhou, Zhiyang Dou, Zeyu Cao +7
We introduce Efficient Motion Diffusion Model (EMDM) for fast and high-quality human motion generation. Current state-of-the-art generative diffusion models have produced impressiv…