Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Ego-Exo: Transferring Visual Representations from Third-person to
  First-person Videos   We introduce an approach for pre-training egocentric video models using
large-scale third-person video datasets. Learning from purely egocentric data
is limited by low dataset scale and diversity, while using purely exocentric
(third-person) data introduces a large domain mismatch. Our idea is to discover
latent signals in third-person video that are predictive of key
egocentric-specific properties. Incorporating these signals as knowledge
distillation losses during pre-training results in models that benefit from
both the scale and diversity of third-person video data, as well as
representations that capture salient egocentric properties. Our experiments
show that our Ego-Exo framework can be seamlessly integrated into standard
video models; it outperforms all baselines when fine-tuned for egocentric
activity recognition, achieving state-of-the-art results on Charades-Ego and
EPIC-Kitchens-100.

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The categories of this paper are: astro-ph
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The categories of this paper are: hep-lat
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
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The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
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The categories of this paper are: acc-phys
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The categories of this paper are: physics
10
The categories of this paper are: q-bio
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The categories of this paper are: eess
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The categories of this paper are: nucl-th
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The categories of this paper are: q-fin
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The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
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The categories of this paper are: funct-an
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The categories of this paper are: atom-ph