We present an approach for inferring complete depth maps from intensity images and sparse depth information. This paper developed prior work which incrementally completes a sparse...
This paper addresses the probabilistic inference of geometric structures from images. Specifically, of synthesizing range data to enhance the reconstruction of a 3D model of an in...
In a popular visual illusion, the portrait on paper currency is folded into an M shape along vertical lines through the nose and the eyes. When this folded picture is tilted back ...
In this work we recover the 3D shape of mirroring objects such as mirrors, sunglasses, and stainless steel objects. A computer monitor displays several images of parallel stripes,...
Stas Rozenfeld, Ilan Shimshoni, Michael Lindenbaum
We present a novel variational approach to estimate dense depth maps from multiple images in real-time. By using robust penalizers for both data term and regularizer, our method pr...