activity
20182024
most citedDeep-NFA: a Deep Framework for Small Object Detection

23 citations · 31 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2024★ 2 cited

ICPR 2024 Competition on Domain Adaptation and GEneralization for Character Classification (DAGECC)

Sofia Marino, Jennifer Vandoni, Emanuel Aldea +3

In this companion paper for the DAGECC (Domain Adaptation and GEneralization for Character Classification) competition organized within the frame of the ICPR 2024 conference, we pr…

cs.CV2023★ 23 cited

Deep-NFA: a Deep Framework for Small Object Detection

Alina Ciocarlan, Sylvie Le Hegarat-Mascle, Sidonie Lefebvre +1

The detection of small objects is a challenging task in computer vision. Conventional object detection methods have difficulty in finding the balance between high detection and low…

cs.CV2019

Evaluating Crowd Density Estimators via Their Uncertainty Bounds

Jennifer Vandoni, Emanuel Aldea, Sylvie Le Hégarat-Mascle

In this work, we use the Belief Function Theory which extends the probabilistic framework in order to provide uncertainty bounds to different categories of crowd density estimators…

cs.CV2018★ 6 cited

Geometry-Based Multiple Camera Head Detection in Dense Crowds

Nicola Pellicanò, Emanuel Aldea, Sylvie Le Hégarat-Mascle

This paper addresses the problem of head detection in crowded environments. Our detection is based entirely on the geometric consistency across cameras with overlapping fields of v…

cs.AI2018

2CoBel : An Efficient Belief Function Extension for Two-dimensional Continuous Spaces

Nicola Pellicanò, Sylvie Le Hégarat-Mascle, Emanuel Aldea

This paper introduces an innovative approach for handling 2D compound hypotheses within the Belief Function Theory framework. We propose a polygon-based generic rep- resentation wh…