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Shentong Mo

53 papers hereh-index 221.8k citations64 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author39
  • middle author12
  • last author1

Across the 53 of 53 papers where every author was matched, so the position is known.

fields
  • cs.CV37
  • cs.LG9
  • cs.SD4
  • cs.CL1
  • q-bio.BM1
  • q-bio.GN1
same name
  • Shentong Mo — 9 papers, h 2
  • Shentong Mo — 3 papers, h 3
  • Shentong Mo — 2 papers, h 5
  • Shentong Mo — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202026
most citedA Closer Look at Weakly-Supervised Audio-Visual Source Localization

21 citations · 138 across the 53 of their papers we have counts for

collaborators
Showing cs.SDShow all

4 papers · 1 filter

cs.SD2024

Semantic Grouping Network for Audio Source Separation

Shentong Mo, Yapeng Tian

Recently, audio-visual separation approaches have taken advantage of the natural synchronization between the two modalities to boost audio source separation performance. They extra…

cs.SD2024★ 2 cited

Text-to-Audio Generation Synchronized with Videos

Shentong Mo, Jing Shi, Yapeng Tian

In recent times, the focus on text-to-audio (TTA) generation has intensified, as researchers strive to synthesize audio from textual descriptions. However, most existing methods, t…

cs.SD2023★ 6 cited

A Unified Audio-Visual Learning Framework for Localization, Separation, and Recognition

Shentong Mo, Pedro Morgado

The ability to accurately recognize, localize and separate sound sources is fundamental to any audio-visual perception task. Historically, these abilities were tackled separately,…

cs.SD2022★ 21 cited

A Closer Look at Weakly-Supervised Audio-Visual Source Localization

Shentong Mo, Pedro Morgado

Audio-visual source localization is a challenging task that aims to predict the location of visual sound sources in a video. Since collecting ground-truth annotations of sounding o…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.