15 citations · 30 across the 5 of their papers we have counts for
5 papers · 1 filter
From Local Geometry to Global Pseudo Labeling for Robust Positive Unlabeled Learning under Covariate Shift
Firas Gabetni, Alexandre Rocchi, Nacim Belkhir +2
Detecting covariate shift is critical for building reliable vision systems. While most prior work focuses on improving robustness to shift, explicitly detecting covariate shift rem…
InfraParis: A multi-modal and multi-task autonomous driving dataset
Gianni Franchi, Marwane Hariat, Xuanlong Yu +3
Current deep neural networks (DNNs) for autonomous driving computer vision are typically trained on specific datasets that only involve a single type of data and urban scenes. Cons…
A study of deep perceptual metrics for image quality assessment
Rémi Kazmierczak, Gianni Franchi, Nacim Belkhir +2
Several metrics exist to quantify the similarity between images, but they are inefficient when it comes to measure the similarity of highly distorted images. In this work, we propo…
Robust Semantic Segmentation with Superpixel-Mix
Gianni Franchi, Nacim Belkhir, Mai Lan Ha +4
Along with predictive performance and runtime speed, reliability is a key requirement for real-world semantic segmentation. Reliability encompasses robustness, predictive uncertain…
Learning Deep Morphological Networks with Neural Architecture Search
Yufei Hu, Nacim Belkhir, Jesus Angulo +2
Deep Neural Networks (DNNs) are generated by sequentially performing linear and non-linear processes. Using a combination of linear and non-linear procedures is critical for genera…