1 code implementation • ICCV 2023 • Shyam Nandan Rai, Fabio Cermelli, Dario Fontanel, Carlo Masone, Barbara Caputo
We propose a paradigm change by shifting from a per-pixel classification to a mask classification.
Ranked #1 on Scene Segmentation on StreetHazards (using extra training data)
no code implementations • 24 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.
1 code implementation • 19 Apr 2022 • Fabio Cermelli, Antonino Geraci, Dario Fontanel, Barbara Caputo
We propose to handle these missing annotations by revisiting the standard knowledge distillation framework.
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.
1 code implementation • 9 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.
1 code implementation • 1 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.
no code implementations • 20 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.