27,764 research outputs found
Clothing Co-Parsing by Joint Image Segmentation and Labeling
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 configurations. We propose a data-driven framework
consisting of two phases of inference. The first phase, referred as "image
co-segmentation", iterates to extract consistent regions on images and jointly
refines the regions over all images by employing the exemplar-SVM (E-SVM)
technique [23]. In the second phase (i.e. "region co-labeling"), we construct a
multi-image graphical model by taking the segmented regions as vertices, and
incorporate several contexts of clothing configuration (e.g., item location and
mutual interactions). The joint label assignment can be solved using the
efficient Graph Cuts algorithm. In addition to evaluate our framework on the
Fashionista dataset [30], we construct a dataset called CCP consisting of 2098
high-resolution street fashion photos to demonstrate the performance of our
system. We achieve 90.29% / 88.23% segmentation accuracy and 65.52% / 63.89%
recognition rate on the Fashionista and the CCP datasets, respectively, which
are superior compared with state-of-the-art methods.Comment: 8 pages, 5 figures, CVPR 201
Massive Dirac surface states in topological insulator/magnetic insulator heterostructures
Topological insulators are new states of matter with a bulk gap and robust
gapless surface states protected by time-reversal symmetry. When time-reversal
symmetry is broken, the surface states are gapped, which induces a topological
response of the system to electromagnetic field--the topological
magnetoelectric effect. In this paper we study the behavior of topological
surface states in heterostructures formed by a topological insulator and a
magnetic insulator. Several magnetic insulators with compatible magnetic
structure and relatively good lattice matching with topological insulators
are identified, and the best
candidate material is found to be MnSe, an anti-ferromagnetic insulator. We
perform first-principles calculation in superlattices and
obtain the surface state bandstructure. The magnetic exchange coupling with
MnSe induces a gap of 54 meV at the surface states. In addition we tune
the distance between Mn ions and TI surface to study the distance dependence of
the exchange coupling.Comment: 8 pages, 7 figure
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