8 citations · 16 across the 9 of their papers we have counts for
9 papers
Event Detection in Videos: A Framework for the Development of New Methods
Anastasia Zakharova, Thierry Bouwmans, Anthony Cioppa +13
Event detection tasks in videos, the most important aspect of video surveillance, aim to detect events either at the pixel-level, frame-level, or clip-level. Plenty of methods inte…
A Methodology to Evaluate Strategies Predicting Rankings on Unseen Domains
Sébastien Piérard, Adrien Deliège, Anaïs Halin +1
Frequently, multiple entities (methods, algorithms, procedures, solutions, etc.) can be developed for a common task and applied across various domains that differ in the distributi…
The Tile: A 2D Map of Ranking Scores for Two-Class Classification
Sébastien Piérard, Anaïs Halin, Anthony Cioppa +2
In the computer vision and machine learning communities, as well as in many other research domains, rigorous evaluation of any new method, including classifiers, is essential. One…
A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers
Anaïs Halin, Sébastien Piérard, Anthony Cioppa +1
Properly understanding the performances of classifiers is essential in various scenarios. However, the literature often relies only on one or two standard scores to compare classif…
Foundations of the Theory of Performance-Based Ranking
Sébastien Piérard, Anaïs Halin, Anthony Cioppa +2
Ranking entities such as algorithms, devices, methods, or models based on their performances, while accounting for application-specific preferences, is a challenge. To address this…
Physically Interpretable Probabilistic Domain Characterization
Anaïs Halin, Sébastien Piérard, Renaud Vandeghen +10
Characterizing domains is essential for models analyzing dynamic environments, as it allows them to adapt to evolving conditions or to hand the task over to backup systems when fac…
Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance
Sébastien Piérard, Anthony Cioppa, Anaïs Halin +5
Various tasks encountered in real-world surveillance can be addressed by determining posteriors (e.g. by Bayesian inference or machine learning), based on which critical decisions…
An exploration of the performances achievable by combining unsupervised background subtraction algorithms
Sébastien Piérard, Marc Braham, Marc Van Droogenbroeck
Background subtraction (BGS) is a common choice for performing motion detection in video. Hundreds of BGS algorithms are released every year, but combining them to detect motion re…
Summarizing the performances of a background subtraction algorithm measured on several videos
Sébastien Piérard, Marc Van Droogenbroeck
There exist many background subtraction algorithms to detect motion in videos. To help comparing them, datasets with ground-truth data such as CDNET or LASIESTA have been proposed.…