3 citations · 5 across the 3 of their papers we have counts for
5 papers · 1 filter
Unmasking Anomalies in Road-Scene Segmentation
Shyam Nandan Rai, Fabio Cermelli, Dario Fontanel +2
Anomaly segmentation is a critical task for driving applications, and it is approached traditionally as a per-pixel classification problem. However, reasoning individually about ea…
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…
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…
Boosting Deep Open World Recognition by Clustering
Dario Fontanel, Fabio Cermelli, Massimiliano Mancini +3
While convolutional neural networks have brought significant advances in robot vision, their ability is often limited to closed world scenarios, where the number of semantic concep…