Search Results for author: Dario Fontanel

Found 7 papers, 5 papers with code

Detecting the unknown in Object Detection

no code implementations24 Aug 2022 Dario Fontanel, Matteo Tarantino, Fabio Cermelli, Barbara Caputo

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 datasets.

Object object-detection +1

Incremental Learning in Semantic Segmentation from Image Labels

1 code implementation CVPR 2022 Fabio Cermelli, Dario Fontanel, Antonio Tavera, Marco Ciccone, Barbara Caputo

As opposed to existing approaches, that need to generate pseudo-labels offline, we use an auxiliary classifier, trained with image-level labels and regularized by the segmentation model, to obtain pseudo-supervision online and update the model incrementally.

Incremental Learning Segmentation +1

On the Challenges of Open World Recognitionunder Shifting Visual Domains

1 code implementation9 Jul 2021 Dario Fontanel, Fabio Cermelli, Massimiliano Mancini, Barbara Caputo

Robotic visual systems operating in the wild must act in unconstrained scenarios, under different environmental conditions while facing a variety of semantic concepts, including unknown ones.

Domain Generalization Object Recognition

Detecting Anomalies in Semantic Segmentation with Prototypes

1 code implementation1 Jun 2021 Dario Fontanel, Fabio Cermelli, Massimiliano Mancini, Barbara Caputo

Current state of the art of anomaly segmentation uses generative models, exploiting their incapability to reconstruct patterns unseen during training.

Segmentation Semantic Segmentation

Boosting Deep Open World Recognition by Clustering

no code implementations20 Apr 2020 Dario Fontanel, Fabio Cermelli, Massimiliano Mancini, Samuel Rota Bulò, Elisa Ricci, Barbara Caputo

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 concepts to be recognized is determined by the available training set.

Clustering Incremental Learning +1

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