7 citations · 14 across the 3 of their papers we have counts for
5 papers
Temporally-Consistent Surface Reconstruction using Metrically-Consistent Atlases
Jan Bednarik, Noam Aigerman, Vladimir G. Kim +4
We propose a method for unsupervised reconstruction of a temporally-consistent sequence of surfaces from a sequence of time-evolving point clouds. It yields dense and semantically…
Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases
Jan Bednarik, Vladimir G. Kim, Siddhartha Chaudhuri +4
We propose a method for the unsupervised reconstruction of a temporally-coherent sequence of surfaces from a sequence of time-evolving point clouds, yielding dense, semantically me…
Better Patch Stitching for Parametric Surface Reconstruction
Zhantao Deng, Jan Bednařík, Mathieu Salzmann +1
Recently, parametric mappings have emerged as highly effective surface representations, yielding low reconstruction error. In particular, the latest works represent the target shap…
Shape Reconstruction by Learning Differentiable Surface Representations
Jan Bednarik, Shaifali Parashar, Erhan Gundogdu +2
Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces, and the best current ones rely on learning an ensemble of parametric represent…
Learning to Reconstruct Texture-less Deformable Surfaces from a Single View
Jan Bednařík, Pascal Fua, Mathieu Salzmann
Recent years have seen the development of mature solutions for reconstructing deformable surfaces from a single image, provided that they are relatively well-textured. By contrast,…