We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
This paper studies the inference of 3D shape from a set of ? noisy photos. We derive a probabilistic framework to specify what one can infer about 3D shape for arbitrarily-shaped, ...
Rahul Bhotika, David J. Fleet, Kiriakos N. Kutulak...
We propose a novel method for reconstructing a complete 3D model of a given anatomy from minimal information. This reconstruction provides an appropriate intra-operative 3D visual...
Energy costs are quickly rising in large-scale data centers and are soon projected to overtake the cost of hardware. As a result, data center operators have recently started turni...
Stavros Harizopoulos, Mehul A. Shah, Justin Meza, ...
The present paper focuses on efficient inverse rendering using a Photometric Stereo technique for realistic surfaces. The technique primarily assumes the Lambertian reflection mod...