no code implementations • 29 Feb 2024 • Vivek Singh, Shailza Sharma, Fabio Cuzzolin
This paper presents a novel feature-boosting network that gathers spatial context from multiple levels of feature extraction and computes the attention weights for each level of representation to generate the final class labels.
no code implementations • 22 Feb 2024 • Fabio Cuzzolin
The purpose of this paper is to look into how central notions in statistical learning theory, such as realisability, generalise under the assumption that train and test distribution are issued from the same credal set, i. e., a convex set of probability distributions.
no code implementations • 1 Feb 2024 • Michele Caprio, Maryam Sultana, Eleni Elia, Fabio Cuzzolin
Statistical learning theory is the foundation of machine learning, providing theoretical bounds for the risk of models learnt from a (single) training set, assumed to issue from an unknown probability distribution.
no code implementations • 10 Jan 2024 • Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal, Fabio Cuzzolin, David Moens, Hans Hallez
Uncertainty estimation is increasingly attractive for improving the reliability of neural networks.
no code implementations • 19 Dec 2023 • Fabio Cuzzolin
In this paper, we discuss a potential agenda for future work in the theory of random sets and belief functions, touching upon a number of focal issues: the development of a fully-fledged theory of statistical reasoning with random sets, including the generalisation of logistic regression and of the classical laws of probability; the further development of the geometric approach to uncertainty, to include general random sets, a wider range of uncertainty measures and alternative geometric representations; the application of this new theory to high-impact areas such as climate change, machine learning and statistical learning theory.
no code implementations • 26 Oct 2023 • Salman Khan, Izzeddin Teeti, Andrew Bradley, Mohamed Elhoseiny, Fabio Cuzzolin
Attention is then applied to this graph to obtain an overall representation of the local dynamic scene.
no code implementations • 8 Aug 2023 • Izzeddin Teeti, Rongali Sai Bhargav, Vivek Singh, Andrew Bradley, Biplab Banerjee, Fabio Cuzzolin
The emerging field of action prediction plays a vital role in various computer vision applications such as autonomous driving, activity analysis and human-computer interaction.
no code implementations • 11 Jul 2023 • Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar, Fabio Cuzzolin
Machine learning is increasingly deployed in safety-critical domains where robustness against adversarial attacks is crucial and erroneous predictions could lead to potentially catastrophic consequences.
1 code implementation • 4 Oct 2022 • Eleonora Giunchiglia, Mihaela Cătălina Stoian, Salman Khan, Fabio Cuzzolin, Thomas Lukasiewicz
Neural networks have proven to be very powerful at computer vision tasks.
no code implementations • 12 Sep 2022 • Kaizhe Jin, Adrian Rubio-Solis, Ravi Naik, Tochukwu Onyeogulu, Amirul Islam, Salman Khan, Izzeddin Teeti, James Kinross, Daniel R Leff, Fabio Cuzzolin, George Mylonas
In this paper, a cascade of two machine learning approaches is suggested for the multimodal recognition of CWL in four different surgical task conditions.
no code implementations • 12 Sep 2022 • Tochukwu Onyeogulu, Salman Khan, Izzeddin Teeti, Amirul Islam, Kaizhe Jin, Adrian Rubio-Solis, Ravi Naik, George Mylonas, Fabio Cuzzolin
Nowadays, there are more surgical procedures that are being performed using minimally invasive surgery (MIS).
no code implementations • 15 Jun 2022 • Shireen Kudukkil Manchingal, Fabio Cuzzolin
The belief function approach to uncertainty quantification as proposed in the Demspter-Shafer theory of evidence is established upon the general mathematical models for set-valued observations, called random sets.
no code implementations • 10 Jan 2022 • Izzeddin Teeti, Valentina Musat, Salman Khan, Alexander Rast, Fabio Cuzzolin, Andrew Bradley
In an autonomous driving system, perception - identification of features and objects from the environment - is crucial.
no code implementations • 5 Jan 2022 • Fabio Cuzzolin
Probability intervals are an attractive tool for reasoning under uncertainty.
no code implementations • 22 Dec 2021 • Aduen Benjumea, Izzeddin Teeti, Fabio Cuzzolin, Andrew Bradley
As autonomous vehicles and autonomous racing rise in popularity, so does the need for faster and more accurate detectors.
no code implementations • 27 Oct 2021 • Ajmal Shahbaz, Salman Khan, Mohammad Asiful Hossain, Vincenzo Lomonaco, Kevin Cannons, Zhan Xu, Fabio Cuzzolin
The aim of this paper is to formalize a new continual semi-supervised learning (CSSL) paradigm, proposed to the attention of the machine learning community via the IJCAI 2021 International Workshop on Continual Semi-Supervised Learning (CSSL-IJCAI), with the aim of raising field awareness about this problem and mobilizing its effort in this direction.
no code implementations • 22 Apr 2021 • Dinesh Jackson Samuel, Fabio Cuzzolin
Anomaly detection in Minimally-Invasive Surgery (MIS) traditionally requires a human expert monitoring the procedure from a console.
no code implementations • 21 Apr 2021 • Fabio Cuzzolin
Conditioning is crucial in applied science when inference involving time series is involved.
no code implementations • 16 Apr 2021 • Salman Khan, Fabio Cuzzolin
We also contribute fresh temporal complex activity annotation for the recently released ROAD autonomous driving and SARAS-ESAD surgical action datasets and show the adaptability of our framework to different domains.
no code implementations • 14 Apr 2021 • Fabio Cuzzolin
Probability theory is far from being the most general mathematical theory of uncertainty.
no code implementations • 7 Apr 2021 • Vivek Singh Bawa, Gurkirt Singh, Francis KapingA, Inna Skarga-Bandurova, Elettra Oleari, Alice Leporini, Carmela Landolfo, Pengfei Zhao, Xi Xiang, Gongning Luo, Kuanquan Wang, Liangzhi Li, Bowen Wang, Shang Zhao, Li Li, Armando Stabile, Francesco Setti, Riccardo Muradore, Fabio Cuzzolin
For an autonomous robotic system, monitoring surgeon actions and assisting the main surgeon during a procedure can be very challenging.
4 code implementations • 1 Apr 2021 • Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido van de Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German I. Parisi, Fabio Cuzzolin, Andreas Tolias, Simone Scardapane, Luca Antiga, Subutai Amhad, Adrian Popescu, Christopher Kanan, Joost Van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni
Learning continually from non-stationary data streams is a long-standing goal and a challenging problem in machine learning.
2 code implementations • 23 Feb 2021 • Gurkirt Singh, Stephen Akrigg, Manuele Di Maio, Valentina Fontana, Reza Javanmard Alitappeh, Suman Saha, Kossar Jeddisaravi, Farzad Yousefi, Jacob Culley, Tom Nicholson, Jordan Omokeowa, Salman Khan, Stanislao Grazioso, Andrew Bradley, Giuseppe Di Gironimo, Fabio Cuzzolin
We also report the performance on the ROAD tasks of Slowfast and YOLOv5 detectors, as well as that of the winners of the ICCV2021 ROAD challenge, which highlight the challenges faced by situation awareness in autonomous driving.
no code implementations • 14 Dec 2020 • Diana Mateus, Radu Horaud, David Knossow, Fabio Cuzzolin, Edmond Boyer
Matching articulated shapes represented by voxel-sets reduces to maximal sub-graph isomorphism when each set is described by a weighted graph.
no code implementations • 12 Jun 2020 • Vivek Singh Bawa, Gurkirt Singh, Francis KapingA, InnaSkarga-Bandurova, Alice Leporini, Carmela Landolfo, Armando Stabile, Francesco Setti, Riccardo Muradore, Elettra Oleari, Fabio Cuzzolin
In this work, we take aim towards increasing the effectiveness of surgical assistant robots.
no code implementations • 13 Apr 2020 • Neha Bhargava, Fabio Cuzzolin
In this paper, we explore some of the applications of computer vision to sports analytics.
1 code implementation • 3 Apr 2020 • Suman Saha, Gurkirt Singh, Fabio Cuzzolin
This is achieved by augmenting the previous Action Micro-Tube (AMTnet) action detection framework in three distinct ways: by adding a parallel motion stIn this paper, we propose a new deep neural network architecture for online action detection, termed ream to the original appearance one in AMTnet; (2) in opposition to state-of-the-art action detectors which train appearance and motion streams separately, and use a test time late fusion scheme to fuse RGB and flow cues, by jointly training both streams in an end-to-end fashion and merging RGB and optical flow features at training time; (3) by introducing an online action tube generation algorithm which works at video-level, and in real-time (when exploiting only appearance features).
no code implementations • 10 Dec 2019 • Hong Zhu, Dongmei Liu, Ian Bayley, Rachel Harrison, Fabio Cuzzolin
With the rapid growth of the applications of machine learning (ML) and other artificial intelligence (AI) techniques, adequate testing has become a necessity to ensure their quality.
no code implementations • 6 May 2019 • Kurt Degiorgio, Fabio Cuzzolin
Enabling computational systems with the ability to localize actions in video-based content has manifold applications.
no code implementations • 4 Apr 2019 • Silvio Olivastri, Gurkirt Singh, Fabio Cuzzolin
The decoder is then optimised on such static features to generate the video's description.
no code implementations • 17 Nov 2018 • Gurkirt Singh, Fabio Cuzzolin
Recently, three dimensional (3D) convolutional neural networks (CNNs) have emerged as dominant methods to capture spatiotemporal representations in videos, by adding to pre-existing 2D CNNs a third, temporal dimension.
no code implementations • 23 Aug 2018 • Gurkirt Singh, Suman Saha, Fabio Cuzzolin
In this work, we present a method to predict an entire `action tube' (a set of temporally linked bounding boxes) in a trimmed video just by observing a smaller subset of it.
no code implementations • 7 Aug 2018 • Fabio Cuzzolin
The notion of belief likelihood function of repeated trials is introduced, whenever the uncertainty for individual trials is encoded by a belief measure (a finite random set).
1 code implementation • 1 Aug 2018 • Gurkirt Singh, Suman Saha, Fabio Cuzzolin
At training time, transitions are specific to cell locations of the feature maps, so that a sparse (efficient) transition matrix is used to train the network.
no code implementations • 30 Jul 2018 • Valentina Fontana, Gurkirt Singh, Stephen Akrigg, Manuele Di Maio, Suman Saha, Fabio Cuzzolin
We present the new Road Event and Activity Detection (READ) dataset, designed and created from an autonomous vehicle perspective to take action detection challenges to autonomous driving.
no code implementations • 22 Jul 2017 • Suman Saha, Gurkirt Singh, Michael Sapienza, Philip H. S. Torr, Fabio Cuzzolin
Current state-of-the-art human action recognition is focused on the classification of temporally trimmed videos in which only one action occurs per frame.
no code implementations • ICCV 2017 • Suman Saha, Gurkirt Singh, Fabio Cuzzolin
As such, our 3D-RPN net is able to effectively encode the temporal aspect of actions by purely exploiting appearance, as opposed to methods which heavily rely on expensive flow maps.
1 code implementation • 5 Apr 2017 • Harkirat Singh Behl, Michael Sapienza, Gurkirt Singh, Suman Saha, Fabio Cuzzolin, Philip H. S. Torr
In this work, we introduce a real-time and online joint-labelling and association algorithm for action detection that can incrementally construct space-time action tubes on the most challenging action videos in which different action categories occur concurrently.
4 code implementations • ICCV 2017 • Gurkirt Singh, Suman Saha, Michael Sapienza, Philip Torr, Fabio Cuzzolin
To the best of our knowledge, ours is the first real-time (up to 40fps) system able to perform online S/T action localisation and early action prediction on the untrimmed videos of UCF101-24.
no code implementations • 4 Aug 2016 • Suman Saha, Gurkirt Singh, Michael Sapienza, Philip H. S. Torr, Fabio Cuzzolin
In stage 2, the appearance network detections are boosted by combining them with the motion detection scores, in proportion to their respective spatial overlap.
1 code implementation • 7 Jul 2016 • Gurkirt Singh, Fabio Cuzzolin
We propose a simple, yet effective, method for the temporal detection of activities in temporally untrimmed videos with the help of untrimmed classification.
no code implementations • 11 Apr 2016 • Rocco De Rosa, Ilaria Gori, Fabio Cuzzolin, Barbara Caputo, Nicolò Cesa-Bianchi
Recognising human activities from streaming videos poses unique challenges to learning algorithms: predictive models need to be scalable, incrementally trainable, and must remain bounded in size even when the data stream is arbitrarily long.
no code implementations • 30 Jul 2014 • Fabio Cuzzolin
Consistent belief functions represent collections of coherent or non-contradictory pieces of evidence, but most of all they are the counterparts of consistent knowledge bases in belief calculus.
no code implementations • 29 May 2014 • Michael Sapienza, Fabio Cuzzolin, Philip H. S. Torr
The recent trend in action recognition is towards larger datasets, an increasing number of action classes and larger visual vocabularies.
no code implementations • 26 May 2014 • Fabio Cuzzolin, Diana Mateus, Radu Horaud
In an unsupervised context, i. e., no prior model of the moving object(s) is available, such a structure has to be learned from the data in a bottom-up fashion.