Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse   In this paper, we propose a new multi-scale face detector having an extremely
tiny number of parameters (EXTD),less than 0.1 million, as well as achieving
comparable performance to deep heavy detectors. While existing multi-scale face
detectors extract feature maps with different scales from a single backbone
network, our method generates the feature maps by iteratively reusing a shared
lightweight and shallow backbone network. This iterative sharing of the
backbone network significantly reduces the number of parameters, and also
provides the abstract image semantics captured from the higher stage of the
network layers to the lower-level feature map. The proposed idea is employed by
various model architectures and evaluated by extensive experiments. From the
experiments from WIDER FACE dataset, we show that the proposed face detector
can handle faces with various scale and conditions, and achieved comparable
performance to the more massive face detectors that few hundreds and tens times
heavier in model size and floating point operations.

33
The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
30
The categories of this paper are: q-alg
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex