no code implementations • LREC 2022 • Luna De Bruyne, Akbar Karimi, Orphee De Clercq, Andrea Prati, Veronique Hoste
In this paper, we present a multimodal dataset for Aspect-Based Emotion Analysis (ABEA).
1 code implementation • 21 Feb 2023 • Leonardo Rossi, Vittorio Bernuzzi, Tomaso Fontanini, Massimo Bertozzi, Andrea Prati
The ability to understand the surrounding scene is of paramount importance for Autonomous Vehicles (AVs).
1 code implementation • 21 Jun 2022 • Leonardo Rossi, Akbar Karimi, Andrea Prati
Nowadays, Semi-Supervised Object Detection (SSOD) is a hot topic, since, while it is rather easy to collect images for creating a new dataset, labeling them is still an expensive and time-consuming task.
no code implementations • 21 Jun 2022 • Leonardo Rossi, Marco Valenti, Sara Elisabetta Legler, Andrea Prati
The Instance Segmentation task, an extension of the well-known Object Detection task, is of great help in many areas, such as precision agriculture: being able to automatically identify plant organs and the possible diseases associated with them, allows to effectively scale and automate crop monitoring and its diseases control.
1 code implementation • Findings (EMNLP) 2021 • Akbar Karimi, Leonardo Rossi, Andrea Prati
This is an easier technique to implement for data augmentation than EDA method (Wei and Zou, 2019) with which we compare our results.
no code implementations • 17 Aug 2021 • Runze Li, Tomaso Fontanini, Luca Donati, Andrea Prati, Bir Bhanu
Gradient-based attention modeling has been used widely as a way to visualize and understand convolutional neural networks.
1 code implementation • 3 Apr 2021 • Leonardo Rossi, Akbar Karimi, Andrea Prati
Within the field of instance segmentation, most of the state-of-the-art deep learning networks rely nowadays on cascade architectures, where multiple object detectors are trained sequentially, re-sampling the ground truth at each step.
Ranked #1 on Instance Segmentation on coco minval
1 code implementation • SEMEVAL 2021 • Akbar Karimi, Leonardo Rossi, Andrea Prati
We tackle this problem utilizing a combination of a state-of-the-art pre-trained language model (CharacterBERT) and a traditional bag-of-words technique.
2 code implementations • ICNLSP 2021 • Akbar Karimi, Leonardo Rossi, Andrea Prati
Aspect-Based Sentiment Analysis (ABSA) studies the consumer opinion on the market products.
Ranked #3 on Aspect Extraction on SemEval 2014 Task 4 Sub Task 2
5 code implementations • 28 Apr 2020 • Leonardo Rossi, Akbar Karimi, Andrea Prati
Given the wide diffusion of deep neural network architectures for computer vision tasks, several new applications are nowadays more and more feasible.
Ranked #66 on Instance Segmentation on COCO minival
4 code implementations • 30 Jan 2020 • Akbar Karimi, Leonardo Rossi, Andrea Prati
In this work, we apply adversarial training, which was put forward by Goodfellow et al. (2014), to the post-trained BERT (BERT-PT) language model proposed by Xu et al. (2019) on the two major tasks of Aspect Extraction and Aspect Sentiment Classification in sentiment analysis.
Ranked #4 on Aspect Extraction on SemEval 2014 Task 4 Sub Task 2
no code implementations • 5 Dec 2019 • Tomaso Fontanini, Eleonora Iotti, Luca Donati, Andrea Prati
Above all, producing images belonging to different domains by using a single architecture is a very relevant goal for image generation.
no code implementations • 17 Sep 2019 • Tomaso Fontanini, Eleonora Iotti, Andrea Prati
In recent years, the majority of works on deep-learning-based image colorization have focused on how to make a good use of the enormous datasets currently available.
no code implementations • 19 Aug 2019 • Federico Magliani, Laura Sani, Stefano Cagnoni, Andrea Prati
We propose to use genetic algorithms to find the optimal setting of all the diffusion parameters with respect to retrieval performance for each different dataset.
1 code implementation • 18 Apr 2019 • Federico Magliani, Kevin McGuinness, Eva Mohedano, Andrea Prati
The application of the diffusion in many computer vision and artificial intelligence projects has been shown to give excellent improvements in performance.
no code implementations • 15 Aug 2018 • Federico Magliani, Tomaso Fontanini, Andrea Prati
The recent advances brought by deep learning allowed to improve the performance in image retrieval tasks.
1 code implementation • 22 Jun 2018 • Federico Magliani, Andrea Prati
The landmark recognition problem is far from being solved, but with the use of features extracted from intermediate layers of Convolutional Neural Networks (CNNs), excellent results have been obtained.
1 code implementation • 15 Jun 2018 • Federico Magliani, Tomaso Fontanini, Andrea Prati
It allows to drastically reduce the query time and outperforms the accuracy results compared to the state-of-the-art methods for large-scale landmark recognition.
no code implementations • 16 Feb 2018 • Luca Donati, Simone Cesano, Andrea Prati
Vectorizing hand-drawn sketches is a challenging task, which is of paramount importance for creating CAD vectorized versions for the fashion and creative workflows.
no code implementations • 19 Jun 2017 • Yonatan Tariku Tesfaye, Eyasu Zemene, Andrea Prati, Marcello Pelillo, Mubarak Shah
In this paper, a unified three-layer hierarchical approach for solving tracking problems in multiple non-overlapping cameras is proposed.
no code implementations • 19 Apr 2017 • Federico Magliani, Navid Mahmoudian Bidgoli, Andrea Prati
The current state of the research in landmark recognition highlights the good accuracy which can be achieved by embedding techniques, such as Fisher vector and VLAD.
no code implementations • 4 Feb 2017 • Eyasu Zemene, Yonatan Tariku, Haroon Idrees, Andrea Prati, Marcello Pelillo, Mubarak Shah
We cast the geo-localization as a clustering problem on local image features.