# AVECL-UMONS database for audio-visual event classification and localization

arXiv: https://arxiv.org/abs/2011.01018 · HTML: https://mlsanity.com/paper/2011.01018/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Oct 2020.

## Built on by (most cited first, 2 of 2)

- [STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events](https://mlsanity.com/paper/2306.09126/) (2023)
- [Deep soccer captioning with transformer: dataset, semantics-related losses, and multi-level evaluation](https://mlsanity.com/paper/2202.05728/) (2022)

## Abstract (arXiv)

We introduce the AVECL-UMons dataset for audio-visual event classification and localization in the context of office environments. The audio-visual dataset is composed of 11 event classes recorded at several realistic positions in two different rooms. Two types of sequences are recorded according to the number of events in the sequence. The dataset comprises 2662 unilabel sequences and 2724 multilabel sequences corresponding to a total of 5.24 hours. The dataset is publicly accessible online : https://zenodo.org/record/3965492#.X09wsobgrCI.