Survey and Evaluation of Neural 3D Shape Classification Approaches.

Classification of 3D objects - the selection of a category in which each object belongs - is of great interest in the field of machine learning. Numerous researchers use deep neural networks to address this problem, altering the network architecture and representation of the 3D shape used as an input. To investigate the effectiveness of their approaches, we conduct an extensive survey of existing methods and identify common ideas by which we categorize them into a taxonomy.

A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images.

Few tone mapping operators (TMOs) take color management into consideration, limiting compression to luminance values only. This could lead to changes in image chroma and hues, which are typically managed with a post-processing step. However, current post-processing techniques for tone reproduction do not explicitly consider the target display gamut.