1 code implementation • 5 Dec 2023 • Victor G. Turrisi da Costa, Nicola Dall'Asen, Yiming Wang, Nicu Sebe, Elisa Ricci
Few-shot image classification aims to learn an image classifier using only a small set of labeled examples per class.
1 code implementation • 26 Jul 2022 • Victor G. Turrisi da Costa, Giacomo Zara, Paolo Rota, Thiago Oliveira-Santos, Nicu Sebe, Vittorio Murino, Elisa Ricci
On the other hand, the performance of a model in action recognition is heavily affected by domain shift.
1 code implementation • CVPR 2022 • Enrico Fini, Victor G. Turrisi da Costa, Xavier Alameda-Pineda, Elisa Ricci, Karteek Alahari, Julien Mairal
Self-supervised models have been shown to produce comparable or better visual representations than their supervised counterparts when trained offline on unlabeled data at scale.
5 code implementations • 3 Aug 2021 • Victor G. Turrisi da Costa, Enrico Fini, Moin Nabi, Nicu Sebe, Elisa Ricci
This paper presents solo-learn, a library of self-supervised methods for visual representation learning.
no code implementations • 16 Jul 2019 • Victor G. Turrisi da Costa, Saulo Martiello Mastelini, André C. Ponce de Leon Ferreira de Carvalho, Sylvio Barbon Jr
To increase predictive performance without largely increasing memory and time costs, this paper introduces a novel algorithm, named Online Local Boosting (OLBoost), which can be combined into online decision tree algorithms to improve their predictive performance without modifying the structure of the induced decision trees.