Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-Prototype Networks for Unconstrained Set-based Face Recognition   In this paper, we study the challenging unconstrained set-based face
recognition problem where each subject face is instantiated by a set of media
(images and videos) instead of a single image. Naively aggregating information
from all the media within a set would suffer from the large intra-set variance
caused by heterogeneous factors (e.g., varying media modalities, poses and
illuminations) and fail to learn discriminative face representations. A novel
Multi-Prototype Network (MPNet) model is thus proposed to learn multiple
prototype face representations adaptively from the media sets. Each learned
prototype is representative for the subject face under certain condition in
terms of pose, illumination and media modality. Instead of handcrafting the set
partition for prototype learning, MPNet introduces a Dense SubGraph (DSG)
learning sub-net that implicitly untangles inconsistent media and learns a
number of representative prototypes. Qualitative and quantitative experiments
clearly demonstrate superiority of the proposed model over state-of-the-arts.

30
The categories of this paper are: q-alg
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
11
The categories of this paper are: hep-lat
13
The categories of this paper are: quant-ph
25
The categories of this paper are: patt-sol