Inversion methods, such as Textual Inversion, generate personalized images by
incorporating concepts of interest provided by user images. However, existing methods often …

Active learning has received great interests from researchers due to its ability to reduce the
amount of supervision required for effective learning. As the core component of active …

This paper presents a pilot study that explores the application of active learning, traditionally
studied in the context of discriminative models, to generative models. We specifically focus …

Recent advancements in generative models have significantly impacted content creation,
leading to the emergence of Personalized Content Synthesis (PCS). With a small set of user …

Video hyperlinking is the task of linking two video fragments/clips based on their multi-modal
contents. Specifically, given an anchor video as a query, machine techniques automatically …

Conventional active learning approaches for interactive video/image retrieval usually
assume the query distribution is unknown, as it is difficult to estimate with only a limited …

Searching through large collections of images to find patterns of use or to find sets of
relevant items is difficult, especially when the information to consider is not only the content …

How to build a compact and informative training data set autonomously is crucial for many
real-world learning tasks, especially those with large amount of unlabeled data and high …

In this paper, the Relevance Feedback procedure for Content Based Image Retrieval is
considered as an Exploration-Exploitation approach. The proposed method exploits the …

This chapter focuses on techniques suited for forensic analysis of large image collections. In
digital forensics an investigator is often tasked to analyze a data source containing large …