Fashion is the way we present ourselves to the world and has become one of the world's
largest industries. Fashion, mainly conveyed by vision, has thus attracted much attention …

Travelling is a combination of journey, transportation, travel-time, accommodation, weather,
events, and other aspects which are likely to be experienced by most of the people at some …

Recent advances in clothes recognition have been driven by the construction of clothes
datasets. Existing datasets are limited in the amount of annotations and are difficult to cope …

Superpixels group perceptually similar pixels to create visually meaningful entities while
heavily reducing the number of primitives for subsequent processing steps. As of these …

In this paper, we define a new task, Exact Street to Shop, where our goal is to match a real-
world example of a garment item to the same item in an online shop. This is an extremely …

We propose a novel deep learning method for shadow removal. Inspired by physical models
of shadow formation, we use a linear illumination transformation to model the shadow effects …

In this work, we address the human parsing task with a novel Contextualized Convolutional
Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global …

In this work, the human parsing task, namely decomposing a human image into semantic
fashion/body regions, is formulated as an active template regression (ATR) problem, where …

This work proposes to combine neural networks with the compositional hierarchy of human
bodies for efficient and complete human parsing. We formulate the approach as a neural …

Modeling the human structure is central for human parsing that extracts pixel-wise semantic
information from images. We start with analyzing three types of inference processes over the …