14 citations · 19 across the 5 of their papers we have counts for
11 papers
CoMFormer: Continual Learning in Semantic and Panoptic Segmentation
Fabio Cermelli, Matthieu Cord, Arthur Douillard
Continual learning for segmentation has recently seen increasing interest. However, all previous works focus on narrow semantic segmentation and disregard panoptic segmentation, an…
Modeling Missing Annotations for Incremental Learning in Object Detection
Fabio Cermelli, Antonino Geraci, Dario Fontanel +1
Despite the recent advances in the field of object detection, common architectures are still ill-suited to incrementally detect new categories over time. They are vulnerable to cat…
Modeling the Background for Incremental and Weakly-Supervised Semantic Segmentation
Fabio Cermelli, Massimiliano Mancini, Samuel Rota Buló +2
Deep neural networks have enabled major progresses in semantic segmentation. However, even the most advanced neural architectures suffer from important limitations. First, they are…
Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic Segmentation
Antonio Tavera, Fabio Cermelli, Carlo Masone +1
In this paper we consider the task of semantic segmentation in autonomous driving applications. Specifically, we consider the cross-domain few-shot setting where training can use o…
On the Challenges of Open World Recognitionunder Shifting Visual Domains
Dario Fontanel, Fabio Cermelli, Massimiliano Mancini +1
Robotic visual systems operating in the wild must act in unconstrained scenarios, under different environmental conditions while facing a variety of semantic concepts, including un…
Detecting Anomalies in Semantic Segmentation with Prototypes
Dario Fontanel, Fabio Cermelli, Massimiliano Mancini +1
Traditional semantic segmentation methods can recognize at test time only the classes that are present in the training set. This is a significant limitation, especially for semanti…