110 citations · 323 across the 41 of their papers we have counts for
17 papers · 1 filter
NeuralDome: A Neural Modeling Pipeline on Multi-View Human-Object Interactions
Juze Zhang, Haimin Luo, Hongdi Yang +6
Humans constantly interact with objects in daily life tasks. Capturing such processes and subsequently conducting visual inferences from a fixed viewpoint suffers from occlusions,…
Weakly Supervised 3D Multi-person Pose Estimation for Large-scale Scenes based on Monocular Camera and Single LiDAR
Peishan Cong, Yiteng Xu, Yiming Ren +5
Depth estimation is usually ill-posed and ambiguous for monocular camera-based 3D multi-person pose estimation. Since LiDAR can capture accurate depth information in long-range sce…
Human Performance Modeling and Rendering via Neural Animated Mesh
Fuqiang Zhao, Yuheng Jiang, Kaixin Yao +8
We have recently seen tremendous progress in the neural advances for photo-real human modeling and rendering. However, it's still challenging to integrate them into an existing mes…
NARRATE: A Normal Assisted Free-View Portrait Stylizer
Youjia Wang, Teng Xu, Yiwen Wu +4
In this work, we propose NARRATE, a novel pipeline that enables simultaneously editing portrait lighting and perspective in a photorealistic manner. As a hybrid neural-physical fac…
Mutual Adaptive Reasoning for Monocular 3D Multi-Person Pose Estimation
Juze Zhang, Jingya Wang, Ye Shi +3
Inter-person occlusion and depth ambiguity make estimating the 3D poses of monocular multiple persons as camera-centric coordinates a challenging problem. Typical top-down framewor…
LiDAR-aid Inertial Poser: Large-scale Human Motion Capture by Sparse Inertial and LiDAR Sensors
Yiming Ren, Chengfeng Zhao, Yannan He +5
We propose a multi-sensor fusion method for capturing challenging 3D human motions with accurate consecutive local poses and global trajectories in large-scale scenarios, only usin…
PREF: Phasorial Embedding Fields for Compact Neural Representations
Binbin Huang, Xinhao Yan, Anpei Chen +2
We present an efficient frequency-based neural representation termed PREF: a shallow MLP augmented with a phasor volume that covers significant border spectra than previous Fourier…
LiDARCap: Long-range Marker-less 3D Human Motion Capture with LiDAR Point Clouds
Jialian Li, Jingyi Zhang, Zhiyong Wang +6
Existing motion capture datasets are largely short-range and cannot yet fit the need of long-range applications. We propose LiDARHuman26M, a new human motion capture dataset captur…
NeuralHOFusion: Neural Volumetric Rendering under Human-object Interactions
Yuheng Jiang, Suyi Jiang, Guoxing Sun +5
4D modeling of human-object interactions is critical for numerous applications. However, efficient volumetric capture and rendering of complex interaction scenarios, especially fro…
NeReF: Neural Refractive Field for Fluid Surface Reconstruction and Implicit Representation
Ziyu Wang, Wei Yang, Junming Cao +3
Existing neural reconstruction schemes such as Neural Radiance Field (NeRF) are largely focused on modeling opaque objects. We present a novel neural refractive field(NeReF) to rec…
TensoRF: Tensorial Radiance Fields
Anpei Chen, Zexiang Xu, Andreas Geiger +2
We present TensoRF, a novel approach to model and reconstruct radiance fields. Unlike NeRF that purely uses MLPs, we model the radiance field of a scene as a 4D tensor, which repre…
HybridCap: Inertia-aid Monocular Capture of Challenging Human Motions
Han Liang, Yannan He, Chengfeng Zhao +4
Monocular 3D motion capture (mocap) is beneficial to many applications. The use of a single camera, however, often fails to handle occlusions of different body parts and hence it i…
HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space Using Wearable IMUs and LiDAR
Yudi Dai, Yitai Lin, Chenglu Wen +5
We propose Human-centered 4D Scene Capture (HSC4D) to accurately and efficiently create a dynamic digital world, containing large-scale indoor-outdoor scenes, diverse human motions…
ICARUS: A Specialized Architecture for Neural Radiance Fields Rendering
Chaolin Rao, Huangjie Yu, Haochuan Wan +9
The practical deployment of Neural Radiance Fields (NeRF) in rendering applications faces several challenges, with the most critical one being low rendering speed on even high-end…
Artemis: Articulated Neural Pets with Appearance and Motion synthesis
Haimin Luo, Teng Xu, Yuheng Jiang +6
We, humans, are entering into a virtual era and indeed want to bring animals to the virtual world as well for companion. Yet, computer-generated (CGI) furry animals are limited by…
Video-driven Neural Physically-based Facial Asset for Production
Longwen Zhang, Chuxiao Zeng, Qixuan Zhang +5
Production-level workflows for producing convincing 3D dynamic human faces have long relied on an assortment of labor-intensive tools for geometry and texture generation, motion ca…
NIMBLE: A Non-rigid Hand Model with Bones and Muscles
Yuwei Li, Longwen Zhang, Zesong Qiu +6
Emerging Metaverse applications demand reliable, accurate, and photorealistic reproductions of human hands to perform sophisticated operations as if in the physical world. While re…