activity
20202023
most citedBoosting Deep Open World Recognition by Clustering

23 citations · 34 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2023

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…

cs.CV2022★ 3 cited

Detecting the unknown in Object Detection

Dario Fontanel, Matteo Tarantino, Fabio Cermelli +1

Object detection methods have witnessed impressive improvements in the last years thanks to the design of novel neural network architectures and the availability of large scale dat…

cs.CV2022★ 3 cited

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…

cs.CV2021★ 3 cited

Incremental Learning in Semantic Segmentation from Image Labels

Fabio Cermelli, Dario Fontanel, Antonio Tavera +2

Although existing semantic segmentation approaches achieve impressive results, they still struggle to update their models incrementally as new categories are uncovered. Furthermore…

cs.CV2021★ 2 cited

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…

cs.CV2021

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…

cs.CV2020★ 23 cited

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…