2 citations · 2 across the 5 of their papers we have counts for
5 papers · 1 filter
Conditional Random Fields for Interactive Refinement of Histopathological Predictions
Tiffanie Godelaine, Maxime Zanella, Karim El Khoury +3
Assisting pathologists in the analysis of histopathological images has high clinical value, as it supports cancer detection and staging. In this context, histology foundation model…
Realistic Test-Time Adaptation of Vision-Language Models
Maxime Zanella, Clément Fuchs, Christophe De Vleeschouwer +1
The zero-shot capabilities of Vision-Language Models (VLMs) have been widely leveraged to improve predictive performance. However, previous works on transductive or test-time adapt…
Enhancing Remote Sensing Vision-Language Models for Zero-Shot Scene Classification
Karim El Khoury, Maxime Zanella, Benoît Gérin +5
Vision-Language Models for remote sensing have shown promising uses thanks to their extensive pretraining. However, their conventional usage in zero-shot scene classification metho…
Poly-CAM: High resolution class activation map for convolutional neural networks
Alexandre Englebert, Olivier Cornu, Christophe De Vleeschouwer
The need for Explainable AI is increasing with the development of deep learning. The saliency maps derived from convolutional neural networks generally fail in localizing with accu…
DeepSportLab: a Unified Framework for Ball Detection, Player Instance Segmentation and Pose Estimation in Team Sports Scenes
Seyed Abolfazl Ghasemzadeh, Gabriel Van Zandycke, Maxime Istasse +3
This paper presents a unified framework to (i) locate the ball, (ii) predict the pose, and (iii) segment the instance mask of players in team sports scenes. Those problems are of h…