2 citations · 6 across the 10 of their papers we have counts for
13 papers
Transformers from Compressed Representations
Juan C. Leon Alcazar, Mattia Soldan, Mohammad Saatialsoruji +4
Compressed file formats are the corner stone of efficient data storage and transmission, yet their potential for representation learning remains largely underexplored. We introduce…
OpenTAD: A Unified Framework and Comprehensive Study of Temporal Action Detection
Shuming Liu, Chen Zhao, Fatimah Zohra +10
Temporal action detection (TAD) is a fundamental video understanding task that aims to identify human actions and localize their temporal boundaries in videos. Although this field…
MatchDiffusion: Training-free Generation of Match-cuts
Alejandro Pardo, Fabio Pizzati, Tong Zhang +4
Match-cuts are powerful cinematic tools that create seamless transitions between scenes, delivering strong visual and metaphorical connections. However, crafting match-cuts is a ch…
Generative Timelines for Instructed Visual Assembly
Alejandro Pardo, Jui-Hsien Wang, Bernard Ghanem +3
The objective of this work is to manipulate visual timelines (e.g. a video) through natural language instructions, making complex timeline editing tasks accessible to non-expert or…
Compressed-Language Models for Understanding Compressed File Formats: a JPEG Exploration
Juan C. Pérez, Alejandro Pardo, Mattia Soldan +3
This study investigates whether Compressed-Language Models (CLMs), i.e. language models operating on raw byte streams from Compressed File Formats~(CFFs), can understand files comp…
Towards Automated Movie Trailer Generation
Dawit Mureja Argaw, Mattia Soldan, Alejandro Pardo +4
Movie trailers are an essential tool for promoting films and attracting audiences. However, the process of creating trailers can be time-consuming and expensive. To streamline this…
Test-Time Adaptation for Combating Missing Modalities in Egocentric Videos
Merey Ramazanova, Alejandro Pardo, Bernard Ghanem +1
Understanding videos that contain multiple modalities is crucial, especially in egocentric videos, where combining various sensory inputs significantly improves tasks like action r…
Exploring Missing Modality in Multimodal Egocentric Datasets
Merey Ramazanova, Alejandro Pardo, Humam Alwassel +1
Multimodal video understanding is crucial for analyzing egocentric videos, where integrating multiple sensory signals significantly enhances action recognition and moment localizat…
Evaluation of Test-Time Adaptation Under Computational Time Constraints
Motasem Alfarra, Hani Itani, Alejandro Pardo +6
This paper proposes a novel online evaluation protocol for Test Time Adaptation (TTA) methods, which penalizes slower methods by providing them with fewer samples for adaptation. T…
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…
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…
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…
BAOD: Budget-Aware Object Detection
Alejandro Pardo, Mengmeng Xu, Ali Thabet +2
We study the problem of object detection from a novel perspective in which annotation budget constraints are taken into consideration, appropriately coined Budget Aware Object Dete…