Existing cross-modal hash retrieval methods can simultaneously enhance retrieval speed
and reduce storage space. However, these methods face a major challenge in determining …

In this paper, we present the fourth release of VISIONE, a tool for fast and effective video
search on a large-scale dataset. It includes several search functionalities like text search …

Due to recent advances in pose-estimation methods, human motion can be extracted from a
common video in the form of 3D skeleton sequences. Despite wonderful application …

The objective of image captioning models is to bridge the gap between the visual and
linguistic modalities by generating natural language descriptions that accurately reflect the …

VISIONE is a large-scale video retrieval system that integrates multiple search
functionalities, including free text search, spatial color and object search, visual and …

Image–text matching is a fundamental task in the multimodal research field, connecting
computer vision and natural language processing by aligning visual content with …

Fine-grained representation is fundamental to species classification based on deep
learning, and in this context, cross-modal contrastive learning is an effective method. The …

This paper presents a revised version of the VISIONE video retrieval system, which offers a
wide range of search functionalities, including free text search, spatial color and object …

With the increasing importance of multimedia and multilingual data in online encyclopedias,
novel methods are needed to fill domain gaps and automatically connect different modalities …

This paper conducts a thorough examination of the 12th Video Browser Showdown (VBS)
competition, a well-established international benchmarking campaign for interactive video …