Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: GroupFace: Learning Latent Groups and Constructing Group-based
  Representations for Face Recognition   In the field of face recognition, a model learns to distinguish millions of
face images with fewer dimensional embedding features, and such vast
information may not be properly encoded in the conventional model with a single
branch. We propose a novel face-recognition-specialized architecture called
GroupFace that utilizes multiple group-aware representations, simultaneously,
to improve the quality of the embedding feature. The proposed method provides
self-distributed labels that balance the number of samples belonging to each
group without additional human annotations, and learns the group-aware
representations that can narrow down the search space of the target identity.
We prove the effectiveness of the proposed method by showing extensive ablation
studies and visualizations. All the components of the proposed method can be
trained in an end-to-end manner with a marginal increase of computational
complexity. Finally, the proposed method achieves the state-of-the-art results
with significant improvements in 1:1 face verification and 1:N face
identification tasks on the following public datasets: LFW, YTF, CALFW, CPLFW,
CFP, AgeDB-30, MegaFace, IJB-B and IJB-C.

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The categories of this paper are: hep-ph
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an