Multimodal Neural Databases

Understand

The rise in loosely-structured data available through text, images, and other modalities has called for new ways of querying them.

• Multimedia Information Retrieval has filled this gap and has witnessed exciting progress in recent years.
• Tasks such as search and retrieval of extensive multimedia archives have undergone massive performance improvements, driven to a large extent by recent developments in multimodal deep learning.
• However, methods in this field remain limited in the kinds of queries they support and, in particular, their inability to answer database-like queries.