15 citations · 52 across the 19 of their papers we have counts for
19 papers
E-React: Towards Emotionally Controlled Synthesis of Human Reactions
Chen Zhu, Buzhen Huang, Zijing Wu +2
Emotion serves as an essential component in daily human interactions. Existing human motion generation frameworks do not consider the impact of emotions, which reduces naturalness…
Reconstructing Close Human Interaction with Appearance and Proxemics Reasoning
Buzhen Huang, Chen Li, Chongyang Xu +4
Due to visual ambiguities and inter-person occlusions, existing human pose estimation methods cannot recover plausible close interactions from in-the-wild videos. Even state-of-the…
Adapting Human Mesh Recovery with Vision-Language Feedback
Chongyang Xu, Buzhen Huang, Chengfang Zhang +2
Human mesh recovery can be approached using either regression-based or optimization-based methods. Regression models achieve high pose accuracy but struggle with model-to-image ali…
Simultaneously Recovering Multi-Person Meshes and Multi-View Cameras with Human Semantics
Buzhen Huang, Jingyi Ju, Yuan Shu +1
Dynamic multi-person mesh recovery has broad applications in sports broadcasting, virtual reality, and video games. However, current multi-view frameworks rely on a time-consuming…
Closely Interactive Human Reconstruction with Proxemics and Physics-Guided Adaption
Buzhen Huang, Chen Li, Chongyang Xu +3
Existing multi-person human reconstruction approaches mainly focus on recovering accurate poses or avoiding penetration, but overlook the modeling of close interactions. In this wo…
Knowledge NeRF: Few-shot Novel View Synthesis for Dynamic Articulated Objects
Wenxiao Cai, Xinyue Lei, Xinyu He +2
We present Knowledge NeRF to synthesize novel views for dynamic scenes. Reconstructing dynamic 3D scenes from few sparse views and rendering them from arbitrary perspectives is a c…
CrowdRec: 3D Crowd Reconstruction from Single Color Images
Buzhen Huang, Jingyi Ju, Yangang Wang
This is a technical report for the GigaCrowd challenge. Reconstructing 3D crowds from monocular images is a challenging problem due to mutual occlusions, server depth ambiguity, an…
Reconstructing Groups of People with Hypergraph Relational Reasoning
Buzhen Huang, Jingyi Ju, Zhihao Li +1
Due to the mutual occlusion, severe scale variation, and complex spatial distribution, the current multi-person mesh recovery methods cannot produce accurate absolute body poses an…
Nonrigid Object Contact Estimation With Regional Unwrapping Transformer
Wei Xie, Zimeng Zhao, Shiying Li +2
Acquiring contact patterns between hands and nonrigid objects is a common concern in the vision and robotics community. However, existing learning-based methods focus more on conta…
4D Myocardium Reconstruction with Decoupled Motion and Shape Model
Xiaohan Yuan, Cong Liu, Yangang Wang
Estimating the shape and motion state of the myocardium is essential in diagnosing cardiovascular diseases.However, cine magnetic resonance (CMR) imaging is dominated by 2D slices,…
Reconstructing Interacting Hands with Interaction Prior from Monocular Images
Binghui Zuo, Zimeng Zhao, Wenqian Sun +3
Reconstructing interacting hands from monocular images is indispensable in AR/VR applications. Most existing solutions rely on the accurate localization of each skeleton joint. How…
Physics-Guided Human Motion Capture with Pose Probability Modeling
Jingyi Ju, Buzhen Huang, Chen Zhu +2
Incorporating physics in human motion capture to avoid artifacts like floating, foot sliding, and ground penetration is a promising direction. Existing solutions always adopt kinem…
Synthesizing Physically Plausible Human Motions in 3D Scenes
Liang Pan, Jingbo Wang, Buzhen Huang +4
We present a physics-based character control framework for synthesizing human-scene interactions. Recent advances adopt physics simulation to mitigate artifacts produced by data-dr…
Semi-supervised Hand Appearance Recovery via Structure Disentanglement and Dual Adversarial Discrimination
Zimeng Zhao, Binghui Zuo, Zhiyu Long +1
Enormous hand images with reliable annotations are collected through marker-based MoCap. Unfortunately, degradations caused by markers limit their application in hand appearance re…
HMDO: Markerless Multi-view Hand Manipulation Capture with Deformable Objects
Wei Xie, Zhipeng Yu, Zimeng Zhao +2
We construct the first markerless deformable interaction dataset recording interactive motions of the hands and deformable objects, called HMDO (Hand Manipulation with Deformable O…
Occluded Human Body Capture with Self-Supervised Spatial-Temporal Motion Prior
Buzhen Huang, Yuan Shu, Jingyi Ju +1
Although significant progress has been achieved on monocular maker-less human motion capture in recent years, it is still hard for state-of-the-art methods to obtain satisfactory r…
A causal convolutional neural network for multi-subject motion modeling and generation
Shuaiying Hou, Congyi Wang, Wenlin Zhuang +5
Inspired by the success of WaveNet in multi-subject speech synthesis, we propose a novel neural network based on causal convolutions for multi-subject motion modeling and generatio…
Towards 3D Dance Motion Synthesis and Control
Wenlin Zhuang, Yangang Wang, Joseph Robinson +4
3D human dance motion is a cooperative and elegant social movement. Unlike regular simple locomotion, it is challenging to synthesize artistic dance motions due to the irregularity…
Music2Dance: DanceNet for Music-driven Dance Generation
Wenlin Zhuang, Congyi Wang, Siyu Xia +2
Synthesize human motions from music, i.e., music to dance, is appealing and attracts lots of research interests in recent years. It is challenging due to not only the requirement o…