Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: PoliTO-IIT Submission to the EPIC-KITCHENS-100 Unsupervised Domain
  Adaptation Challenge for Action Recognition   In this report, we describe the technical details of our submission to the
EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action
Recognition. To tackle the domain-shift which exists under the UDA setting, we
first exploited a recent Domain Generalization (DG) technique, called Relative
Norm Alignment (RNA). It consists in designing a model able to generalize well
to any unseen domain, regardless of the possibility to access target data at
training time. Then, in a second phase, we extended the approach to work on
unlabelled target data, allowing the model to adapt to the target distribution
in an unsupervised fashion. For this purpose, we included in our framework
existing UDA algorithms, such as Temporal Attentive Adversarial Adaptation
Network (TA3N), jointly with new multi-stream consistency losses, namely
Temporal Hard Norm Alignment (T-HNA) and Min-Entropy Consistency (MEC). Our
submission (entry 'plnet') is visible on the leaderboard and it achieved the
1st position for 'verb', and the 3rd position for both 'noun' and 'action'.

24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
32
The categories of this paper are: atom-ph
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
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The categories of this paper are: quant-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: patt-sol
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The categories of this paper are: eess
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph