activity
20172024
most citedInterGen: Diffusion-based Multi-human Motion Generation under Complex Interactions

110 citations · 387 across the 42 of their papers we have counts for

collaborators
Showing 2022 · cs.CVShow all

15 papers · 2 filters

cs.CV2022★ 3 cited

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,…

cs.CV2022★ 2 cited

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…

cs.CV2022★ 10 cited

Gait Recognition in Large-scale Free Environment via Single LiDAR

Xiao Han, Yiming Ren, Peishan Cong +4

Human gait recognition is crucial in multimedia, enabling identification through walking patterns without direct interaction, enhancing the integration across various media forms i…

cs.CV2022★ 1 cited

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…

cs.CV2022★ 3 cited

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…

cs.CV2022★ 52 cited

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…

cs.CV2022★ 4 cited

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…

cs.CV2022

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…

cs.CV2022★ 4 cited

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…

cs.CV2022

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…

cs.CV2022★ 1 cited

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…

cs.CV2022★ 4 cited

Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-time

Liao Wang, Jiakai Zhang, Xinhang Liu +6

Implicit neural representations such as Neural Radiance Field (NeRF) have focused mainly on modeling static objects captured under multi-view settings where real-time rendering can…

cs.CV2022★ 5 cited

NeuVV: Neural Volumetric Videos with Immersive Rendering and Editing

Jiakai Zhang, Liao Wang, Xinhang Liu +7

Some of the most exciting experiences that Metaverse promises to offer, for instance, live interactions with virtual characters in virtual environments, require real-time photo-rea…

cs.CV2022★ 2 cited

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…

cs.CV2022★ 15 cited

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…