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most citedTexMesh: Reconstructing Detailed Human Texture and Geometry from RGB-D Video

5 citations · 10 across the 5 of their papers we have counts for

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cs.CV20205 cited

TexMesh: Reconstructing Detailed Human Texture and Geometry from RGB-D Video

Tiancheng Zhi, Christoph Lassner, Tony Tung +3

We present TexMesh, a novel approach to reconstruct detailed human meshes with high-resolution full-body texture from RGB-D video. TexMesh enables high quality free-viewpoint rende…

cs.CV2020

Spatiotemporal Bundle Adjustment for Dynamic 3D Human Reconstruction in the Wild

Minh Vo, Yaser Sheikh, Srinivasa G. Narasimhan

Bundle adjustment jointly optimizes camera intrinsics and extrinsics and 3D point triangulation to reconstruct a static scene. The triangulation constraint, however, is invalid for…

cs.CV2020

4D Visualization of Dynamic Events from Unconstrained Multi-View Videos

Aayush Bansal, Minh Vo, Yaser Sheikh +2

We present a data-driven approach for 4D space-time visualization of dynamic events from videos captured by hand-held multiple cameras. Key to our approach is the use of self-super…

cs.CV2019

Neural RGB->D Sensing: Depth and Uncertainty from a Video Camera

Chao Liu, Jinwei Gu, Kihwan Kim +2

Depth sensing is crucial for 3D reconstruction and scene understanding. Active depth sensors provide dense metric measurements, but often suffer from limitations such as restricted…

cs.CV2018

Self-supervised Multi-view Person Association and Its Applications

Minh Vo, Ersin Yumer, Kalyan Sunkavalli +3

Reliable markerless motion tracking of people participating in a complex group activity from multiple moving cameras is challenging due to frequent occlusions, strong viewpoint and…