Recent advancements in deep learning have significantly enhanced content-based retrieval
methods, notably through models like CLIP that map images and texts into a shared …

The way we create, consume and interact with multimedia content has changed significantly
in recent years with the advent of affordable recording devices and easy sharing and access …

Abstract Contrastive Language and Image Pairing (CLIP), a transformative method in
multimedia retrieval, typically trains two neural networks concurrently to generate joint …

Relevance feedback mechanisms have garnered significant attention in content-based
image and video retrieval thanks to their effectiveness in refining search results to better …

Cross-modal representation learning is essential for interactive text-to-video search tasks.
However, the representation learning is limited by the size and quality of video-caption pairs …

We present a third version of the PraK system designed around an effective text-image and
image-image search model. The system integrates sub-image search options for localized …

The rapid growth of the internet and technology has led to an exponential increase in the
volume of information individuals must manage, which results in a rising demand for search …

This paper presents ViFi-a Vi deo Fi nding System for Video Browser Showdown 2025. Our
retrieval system is mainly based on the SigLIP, a most recent and robust visual-textual …

In summary, our innovative retrieval system for interactive video search, developed for the
VBS 2025 competition, significantly elevates the user experience through the utilization of …

It is with great pleasure that we welcome you to the 31st International Conference on
Multimedia Modeling (MMM 2025), held from January 8 to 10, 2025, in the historic city of …