8 accepted papers
The task of Visual Sound Source Localization (VSSL) involves identifying the location of sound sources in visual scenes, integrating audio-visual data for enhanced scene understanding. Despite advancements in state-of-the-art (SOTA) models, we observe three critical flaws: i) The evaluation of the m…
We present SONIQUE, a model for generating background music tailored to video content. Unlike traditional video-to-music generation approaches, which rely heavily on paired audio-visual datasets, SONIQUE leverages unpaired data, combining royalty-free music and independent video sources. By utilizin…
In this paper, we trace the evolution of Music Information Retrieval (MIR) over the past 25 years. While MIR gathers all kinds of research related to music informatics, a large part of it focuses on signal processing techniques for music data, fostering a close relationship with the IEEE Audio and A…
The COVID-19 pandemic had an unprecedented effect in human activity and city landscapes. A very notorious transformation during this period was the change in noise levels and patterns across cities. Small scale studies have show this change in noise levels across different locations in the globe. In…
Most recent work in visual sound source localization relies on semantic audio-visual representations learned in a self-supervised manner and, by design, excludes temporal information present in videos. While it proves to be effective for widely used benchmark datasets, the method falls short for cha…
Self-supervision methods learn representations by solving pretext tasks that do not require human-generated labels, alleviating the need for time-consuming annotations. These methods have been applied in computer vision, natural language processing, environmental sound analysis, and recently in musi…
Automatic audio-visual urban traffic understanding is a growing area of research with many potential applications of value to industry, academia, and the public sector. Yet, the lack of well-curated resources for training and evaluating models to research in this area hinders their development. To a…
In recent years the task of downbeat tracking has received increasing attention and the state of the art has been improved with the introduction of deep learning methods. Among proposed solutions, existing systems exploit short-term musical rules as part of their language modelling. In this work we…