The content-based remote sensing image retrieval (CBRSIR) has recently become a hot
topic due to its wide applications in analysis of remote sensing data. However, since …

In music source separation, the number of sources may vary for each piece and some of the
sources may belong to the same family of instruments, thus sharing timbral characteristics …

In this paper, we tackle sound localization as a natural outcome of the audio-visual video
classification problem. Differently from the existing sound localization approaches, we do not …

Recognizing sounds is a key aspect of computational audio scene analysis and machine
perception. In this paper, we advocate that sound recognition is inherently a multi-modal …

In this work, we study music/video cross-modal recommendation, ie recommending a music
track for a video or vice versa. We rely on a self-supervised learning paradigm to learn from …

Sound source localization in visual scenes is to associate sounds and their visual
producers. Although great progress has been made in this field, the mixed sounds from …

The recent success of transformer models in language, such as BERT, has motivated the
use of such architectures for multi-modal feature learning and tasks. However, most multi …

Acoustic images are an emergent data modality for multimodal scene understanding. Such
images have the peculiarity of distinguishing the spectral signature of the sound coming …

This survey offers a comprehensive review of recent advancements in multimodal alignment
and fusion within machine learning, spurred by the growing diversity of data types such as …

The recent success of transformer models in language, such as BERT, has motivated the
use of such architectures for multi-modal feature learning and tasks. However, most multi …