Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Keypoint based Sign Language Translation without Glosses   Sign Language Translation (SLT) is a task that has not been studied
relatively much compared to the study of Sign Language Recognition (SLR).
However, the SLR is a study that recognizes the unique grammar of sign
language, which is different from the spoken language and has a problem that
non-disabled people cannot easily interpret. So, we're going to solve the
problem of translating directly spoken language in sign language video. To this
end, we propose a new keypoint normalization method for performing translation
based on the skeleton point of the signer and robustly normalizing these points
in sign language translation. It contributed to performance improvement by a
customized normalization method depending on the body parts. In addition, we
propose a stochastic frame selection method that enables frame augmentation and
sampling at the same time. Finally, it is translated into the spoken language
through an Attention-based translation model. Our method can be applied to
various datasets in a way that can be applied to datasets without glosses. In
addition, quantitative experimental evaluation proved the excellence of our
method.

31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math