Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Sound Localization Better From Semantically Similar Samples   The objective of this work is to localize the sound sources in visual scenes.
Existing audio-visual works employ contrastive learning by assigning
corresponding audio-visual pairs from the same source as positives while
randomly mismatched pairs as negatives. However, these negative pairs may
contain semantically matched audio-visual information. Thus, these semantically
correlated pairs, "hard positives", are mistakenly grouped as negatives. Our
key contribution is showing that hard positives can give similar response maps
to the corresponding pairs. Our approach incorporates these hard positives by
adding their response maps into a contrastive learning objective directly. We
demonstrate the effectiveness of our approach on VGG-SS and SoundNet-Flickr
test sets, showing favorable performance to the state-of-the-art methods.

20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph
4
The categories of this paper are: cond-mat
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The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
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The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th