Deep learning has triggered the current rise of artificial intelligence and is the workhorse of
today's machine intelligence. Numerous success stories have rapidly spread all over …

We present LLoVi, a language-based framework for long-range video question-answering
(LVQA). Unlike prior long-range video understanding methods, which are often costly and …

Our objective in this work is the long range understandingof the narrative structure of
movies. Instead of considering the entire movie, we propose to learn from thekey scenes' of …

Egocentric videos provide a unique perspective into individuals' daily experiences, yet their
unstructured nature presents challenges for perception. In this paper, we introduce AMEGO …

Video content creation keeps growing at an incredible pace; yet, creating engaging stories
remains challenging and requires non-trivial video editing expertise. Many video editing …

This paper considers the problem of Multi-Hop Video Question Answering (MH-VidQA) in
long-form egocentric videos. This task not only requires to answer visual questions, but also …

In this paper we propose a new evaluation challenge and direction in the area of High-level
Video Understanding. The challenge we are proposing is designed to test automatic video …

Large language models such as GPT-3 have demonstrated an impressive capability to
adapt to new tasks without requiring task-specific training data. This capability has been …

The human ability of deep cognitive skills is crucial for the development of various real-world
applications that process diverse and abundant user generated input. While recent progress …

Video grounding is a fundamental problem in multimodal content understanding, aiming to
localize specific natural language queries in an untrimmed video. However, current video …