Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Face Detection with Feature Pyramids and Landmarks   Accurate face detection and facial landmark localization are crucial to any
face recognition system. We present a series of three single-stage RCNNs with
different sized backbones (MobileNetV2-25, MobileNetV2-100, and ResNet101) and
a six-layer feature pyramid trained exclusively on the WIDER FACE dataset. We
compare the face detection and landmark accuracies using eight context module
architectures, four proposed by previous research and four modified versions.
We find no evidence that any of the proposed architectures significantly
overperform and postulate that the random initialization of the additional
layers is at least of equal importance. To show this we present a model that
achieves near state-of-the-art performance on WIDER FACE and also provides high
accuracy landmarks with a simple context module. We also present results using
MobileNetV2 backbones, which achieve over 90% average precision on the WIDER
FACE hard validation set while being able to run in real-time. By comparing to
other authors, we show that our models exceed the state-of-the-art for
similar-sized RCNNs and match the performance of much heavier networks.

22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
27
The categories of this paper are: comp-gas
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ