Multi-modal clustering represents a formidable challenge in the domain of unsupervised
learning. The objective of multi-modal clustering is to categorize data collected from diverse …

Advertisements are one of the most important way for companies to access their customers.
In this context, televison commercials are gaining significant importance in many sectors …

Owing to the increased video content consumption in recent years, the need for advanced
contextual advertising methods that leverage increasing user engagement and relevance on …

Video advertising is a thriving industry that has recently turned its attention to the use of
intelligent algorithms for automating tasks. In advertisement insertion, the integration of …

Scene segmentation is the task of segmenting the video in groups of frames with a high
degree of semantic similarity. In this paper, we contribute to the task of video scene …

With the proliferation of Over-the-Top (OTT) content consumption, programmatic advertising
has become a key service, enhancing publishers' revenue via advertisements (ads) …

Within the dynamic landscape of television content, the critical need to automate the
indexing and organization of archives has emerged as a paramount objective. In response …

With the advent of overdriving technologies, the problems faced by computer vision are
rectified with the working process like segmentation, compression, etc. The segmentation …

Video ads segmentation and tagging is a challenging task due to two main reasons:(1) the
video scene structure is complex and (2) it includes multiple modalities (eg, visual, audio …

Videos have become a very important part of higher education institutes. It is integrated as
part of any traditional courses. Even though video lectures are very interesting teaching …