Semantic segmentation, also called scene labeling, refers to the process of assigning a
semantic label (eg car, people, and road) to each pixel of an image. It is an essential data …

Along with the explosive growth of multimedia data, automatic multimedia tagging has
attracted great interest of various research communities, such as computer vision …

This paper aims at developing an integrated system of clothing co-parsing, in order to jointly
parse a set of clothing images (unsegmented but annotated with tags) into semantic …

In this paper we address the problem of automatically parsing the fashion images with weak
supervision from the user-generated color-category tags such as “red jeans” and “white T …

This paper aims at developing an integrated system for clothing co-parsing (CCP), in order
to jointly parse a set of clothing images (unsegmented but annotated with tags) into semantic …

Recent research has shown the initial success of sparse coding (Sc) in solving many
computer vision tasks. Motivated by the fact that kernel trick can capture the nonlinear …

A weakly supervised semantic segmentation (WSSS) method aims to learn a segmentation
model from weak (image-level) as opposed to strong (pixel-level) labels. By avoiding the …

We propose a new, challenging, problem in kinship classification: recognizing the family that
a query person belongs to from a set of families. We propose a novel framework for …

We are living in an Age of Information where the amount of accessible data from science
and culture is almost limitless. However, this also means that finding an item of interest is …

Nowadays numerous social images have been emerging on the Web. How to precisely
label these images is critical to image retrieval. However, traditional image-level tagging …