Depth-map merging approaches have become more and
more popular in multi-view stereo (MVS) because of their
flexibility and superior performance. The quality of depth
map used fo...
Yebin Liu (Tsinghua University), Xun Cao (Tsinghu...
Recognizing object classes and their 3D viewpoints is an
important problem in computer vision. Based on a partbased
probabilistic representation [31], we propose a new
3D object...
We formulate multi-view 3D shape reconstruction as the computation of a minimum cut on the dual graph of a semiregular, multi-resolution, tetrahedral mesh. Our method does not ass...
Sudipta N. Sinha, Philippos Mordohai, Marc Pollefe...
In this paper, we investigate what can be inferred from several silhouette probability maps, in multi-camera environments. To this aim, we propose a new framework for multi-view s...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...