Metric learning aims to measure the similarity among samples while using an optimal
distance metric for learning tasks. Metric learning methods, which generally use a linear …

Deep learning has recently gained popularity achieving state-of-the-art performance in tasks
involving text, sound, or image processing. Due to its outstanding performance, there have …

This paper presents the Dexterity Network (Dex-Net) 1.0, a dataset of 3D object models and
a sampling-based planning algorithm to explore how Cloud Robotics can be used for robust …

Retrieving 3D models from 2D human sketches has received considerable attention in the
areas of graphics, image retrieval, and computer vision. Almost always in state of the art …

Projective analysis is an important solution for 3D shape retrieval, since human visual
perceptions of 3D shapes rely on various 2D observations from different view points …

Recent image retrieval techniques are focusing on multiple image features for the efficient
image retrieval. It has been an inevitable requirement to fetch the images from a variety of …

With the advent of commodity 3D capturing devices and better 3D modeling tools, 3D shape
content is becoming increasingly prevalent. Therefore, the need for shape retrieval …

The recent introduction of 3D shape analysis frameworks able to quantify the deformation of
a shape into another in terms of the variation of real functions yields a new interpretation of …

Deep learning for image retrieval has been used in this era, but image retrieval with the
highest accuracy is the biggest challenge, which still lacks auto-correlation for feature …

Despite the advances in machine learning techniques, similarity assessment among
multimedia data remains a challenging task of broad interest in computer science …