most citedMAD: A Scalable Dataset for Language Grounding in Videos from Movie Audio Descriptions

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2022

PIVOT: Prompting for Video Continual Learning

Andrés Villa, Juan León Alcázar, Motasem Alfarra +5

Modern machine learning pipelines are limited due to data availability, storage quotas, privacy regulations, and expensive annotation processes. These constraints make it difficult…

cs.CV2022★ 1 cited

vCLIMB: A Novel Video Class Incremental Learning Benchmark

Andrés Villa, Kumail Alhamoud, Juan León Alcázar +3

Continual learning (CL) is under-explored in the video domain. The few existing works contain splits with imbalanced class distributions over the tasks, or study the problem in uns…

cs.CV2021★ 2 cited

MAD: A Scalable Dataset for Language Grounding in Videos from Movie Audio Descriptions

Mattia Soldan, Alejandro Pardo, Juan León Alcázar +4

The recent and increasing interest in video-language research has driven the development of large-scale datasets that enable data-intensive machine learning techniques. In comparis…

cs.CV2021

Learning to Cut by Watching Movies

Alejandro Pardo, Fabian Caba Heilbron, Juan León Alcázar +2

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…

cs.CV2021

MovieCuts: A New Dataset and Benchmark for Cut Type Recognition

Alejandro Pardo, Fabian Caba Heilbron, Juan León Alcázar +2

Understanding movies and their structural patterns is a crucial task in decoding the craft of video editing. While previous works have developed tools for general analysis, such as…