3 citations · 8 across the 4 of their papers we have counts for
6 papers
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…
Function4D: Real-time Human Volumetric Capture from Very Sparse Consumer RGBD Sensors
Tao Yu, Zerong Zheng, Kaiwen Guo +3
Human volumetric capture is a long-standing topic in computer vision and computer graphics. Although high-quality results can be achieved using sophisticated off-line systems, real…
HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences
Feitong Tan, Danhang Tang, Mingsong Dou +9
In this paper, we address the problem of building dense correspondences between human images under arbitrary camera viewpoints and body poses. Prior art either assumes small motion…
POSEFusion: Pose-guided Selective Fusion for Single-view Human Volumetric Capture
Zhe Li, Tao Yu, Zerong Zheng +2
We propose POse-guided SElective Fusion (POSEFusion), a single-view human volumetric capture method that leverages tracking-based methods and tracking-free inference to achieve hig…
NeuralHumanFVV: Real-Time Neural Volumetric Human Performance Rendering using RGB Cameras
Xin Suo, Yuheng Jiang, Pei Lin +4
4D reconstruction and rendering of human activities is critical for immersive VR/AR experience.Recent advances still fail to recover fine geometry and texture results with the leve…
DoubleFusion: Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor
Tao Yu, Zerong Zheng, Kaiwen Guo +5
We propose DoubleFusion, a new real-time system that combines volumetric dynamic reconstruction with data-driven template fitting to simultaneously reconstruct detailed geometry, n…