Recent years have seen remarkable advances in visual understanding. However, how to
understand a story-based long video with artistic styles, eg movie, remains challenging. In …

Understanding videos such as TV series and movies requires analyzing who the characters
are and what they are doing. We address the challenging problem of clustering face tracks …

Visual narrative is often a combination of explicit information and judicious omissions,
relying on the viewer to supply missing details. In comics, most movements in time and …

Historically, the principal interest in the typed λ-calculus is in connection with Godel's
functional (" Dialectica") interpretation'of intuitionistic arithmetic. However, since the early …

A good clustering algorithm can discover natural groupings in data. These groupings, if used
wisely, provide a form of weak supervision for learning representations. In this work, we …

The objective of this work is person-clustering in videos--grouping characters according to
their identity. Previous methods focus on the narrower task of face-clustering, and for the …

Analyzing the story behind TV series and movies often requires understanding who the
characters are and what they are doing. With improving deep face models, this may seem …

The task of searching certain people in videos has seen increasing potential in real-world
applications, such as video organization and editing. Most existing approaches are devised …

We present an end-to-end system for detecting and clustering faces by identity in full-length
movies. Unlike works that start with a predefined set of detected faces, we consider the end …

We introduce multimodal story summarization by leveraging TV episode recaps-short video
sequences interweaving key story moments from previous episodes to bring viewers up to …