activity
20232026
most citedLetsGo: Large-Scale Garage Modeling and Rendering via LiDAR-Assisted Gaussian Primitives

40 citations · 48 across the 17 of their papers we have counts for

collaborators

19 papers

cs.GR2026

SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-Based Humanoid Control

Jingyan Zhang, Han Liang, Ruichi Zhang +6

Controlling physics-based humanoids from natural-language instructions is a critical step toward general-purpose embodied agents. However, existing methods remain constrained by a…

cs.CV2025

InterAgent: Physics-based Multi-agent Command Execution via Diffusion on Interaction Graphs

Bin Li, Ruichi Zhang, Han Liang +6

Humanoid agents are expected to emulate the complex coordination inherent in human social behaviors. However, existing methods are largely confined to single-agent scenarios, overl…

cs.CV2025

Towards Immersive Human-X Interaction: A Real-Time Framework for Physically Plausible Motion Synthesis

Kaiyang Ji, Ye Shi, Zichen Jin +5

Real-time synthesis of physically plausible human interactions remains a critical challenge for immersive VR/AR systems and humanoid robotics. While existing methods demonstrate pr…

cs.CV2025

Human-Object Interaction via Automatically Designed VLM-Guided Motion Policy

Zekai Deng, Ye Shi, Kaiyang Ji +3

Human-object interaction (HOI) synthesis is crucial for applications in animation, simulation, and robotics. However, existing approaches either rely on expensive motion capture da…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 40 cited

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…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 1 cited

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.…

cs.CV2024

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…

cs.CV2023

HybridGait: A Benchmark for Spatial-Temporal Cloth-Changing Gait Recognition with Hybrid Explorations

Yilan Dong, Chunlin Yu, Ruiyang Ha +5

Existing gait recognition benchmarks mostly include minor clothing variations in the laboratory environments, but lack persistent changes in appearance over time and space. In this…

cs.CV2023

MVHuman: Tailoring 2D Diffusion with Multi-view Sampling For Realistic 3D Human Generation

Suyi Jiang, Haimin Luo, Haoran Jiang +3

Recent months have witnessed rapid progress in 3D generation based on diffusion models. Most advances require fine-tuning existing 2D Stable Diffsuions into multi-view settings or…

cs.CV2023★ 1 cited

HiFi4G: High-Fidelity Human Performance Rendering via Compact Gaussian Splatting

Yuheng Jiang, Zhehao Shen, Penghao Wang +5

We have recently seen tremendous progress in photo-real human modeling and rendering. Yet, efficiently rendering realistic human performance and integrating it into the rasterizati…

cs.CV2023

OMG: Towards Open-vocabulary Motion Generation via Mixture of Controllers

Han Liang, Jiacheng Bao, Ruichi Zhang +6

We have recently seen tremendous progress in realistic text-to-motion generation. Yet, the existing methods often fail or produce implausible motions with unseen text inputs, which…

cs.CV2023

I'M HOI: Inertia-aware Monocular Capture of 3D Human-Object Interactions

Chengfeng Zhao, Juze Zhang, Jiashen Du +5

We are living in a world surrounded by diverse and "smart" devices with rich modalities of sensing ability. Conveniently capturing the interactions between us humans and these obje…

cs.CV2023★ 1 cited

BOTH2Hands: Inferring 3D Hands from Both Text Prompts and Body Dynamics

Wenqian Zhang, Molin Huang, Yuxuan Zhou +4

The recently emerging text-to-motion advances have spired numerous attempts for convenient and interactive human motion generation. Yet, existing methods are largely limited to gen…

cs.CV2023★ 3 cited

HandDiffuse: Generative Controllers for Two-Hand Interactions via Diffusion Models

Pei Lin, Sihang Xu, Hongdi Yang +5

Existing hands datasets are largely short-range and the interaction is weak due to the self-occlusion and self-similarity of hands, which can not yet fit the need for interacting h…