Search Results for author: Vittorio Murino

Found 62 papers, 18 papers with code

Leveraging Acoustic Images for Effective Self-Supervised Audio Representation Learning

1 code implementation ECCV 2020 Valentina Sanguineti, Pietro Morerio, Niccolò Pozzetti, Danilo Greco, Marco Cristani, Vittorio Murino

However, since 2D planar arrays are cumbersome and not as widespread as ordinary microphones, we propose that the richer information content of acoustic images can be distilled, through a self-supervised learning scheme, into more powerful audio and visual feature representations.

Cross-Modal Retrieval Representation Learning +3

Anticipating Next Active Objects for Egocentric Videos

no code implementations13 Feb 2023 Sanket Thakur, Cigdem Beyan, Pietro Morerio, Vittorio Murino, Alessio Del Bue

This paper addresses the problem of anticipating the next-active-object location in the future, for a given egocentric video clip where the contact might happen, before any action takes place.

From Biased Data to Unbiased Models: a Meta-Learning Approach

no code implementations29 Sep 2021 Ruggero Ragonesi, Valentina Sanguineti, Jacopo Cavazza, Vittorio Murino

It is well known that large deep architectures are powerful models when adequately trained, but may exhibit undesirable behavior leading to confident incorrect predictions, even when evaluated on slightly different test examples.


Compact CNN Structure Learning by Knowledge Distillation

no code implementations19 Apr 2021 Waqar Ahmed, Andrea Zunino, Pietro Morerio, Vittorio Murino

The concept of compressing deep Convolutional Neural Networks (CNNs) is essential to use limited computation, power, and memory resources on embedded devices.

Knowledge Distillation Model Compression

Adaptive Pseudo-Label Refinement by Negative Ensemble Learning for Source-Free Unsupervised Domain Adaptation

no code implementations29 Mar 2021 Waqar Ahmed, Pietro Morerio, Vittorio Murino

On the contrary, a pre-trained source model is always considered to be available, even though performing poorly on target due to the well-known domain shift problem.

Ensemble Learning Pseudo Label +1

Learning without Seeing nor Knowing: Towards Open Zero-Shot Learning

no code implementations23 Mar 2021 Federico Marmoreo, Julio Ivan Davila Carrazco, Vittorio Murino, Jacopo Cavazza

We formalize OZSL as the problem of recognizing seen and unseen classes (as in GZSL) while also rejecting instances from unknown categories, for which neither visual data nor class embeddings are provided.

Generalized Zero-Shot Learning

Transductive Zero-Shot Learning by Decoupled Feature Generation

no code implementations5 Feb 2021 Federico Marmoreo, Jacopo Cavazza, Vittorio Murino

In this paper, we address zero-shot learning (ZSL), the problem of recognizing categories for which no labeled visual data are available during training.

Zero-Shot Learning

A Versatile Crack Inspection Portable System based on Classifier Ensemble and Controlled Illumination

no code implementations19 Oct 2020 Milind G. Padalkar, Carlos Beltrán-González, Matteo Bustreo, Alessio Del Bue, Vittorio Murino

This paper presents a novel setup for automatic visual inspection of cracks in ceramic tile as well as studies the effect of various classifiers and height-varying illumination conditions for this task.

DSLib: An open source library for the dominant set clustering method

1 code implementation15 Oct 2020 Sebastiano Vascon, Samuel Rota Bulò, Vittorio Murino, Marcello Pelillo

This package provides an implementation of the original DS clustering algorithm since no code has been officially released yet, together with a still growing collection of methods and variants related to it.

Graph Matching

The Visual Social Distancing Problem

no code implementations11 May 2020 Marco Cristani, Alessio Del Bue, Vittorio Murino, Francesco Setti, Alessandro Vinciarelli

One of the main and most effective measures to contain the recent viral outbreak is the maintenance of the so-called Social Distancing (SD).

Learning Unbiased Representations via Mutual Information Backpropagation

1 code implementation13 Mar 2020 Ruggero Ragonesi, Riccardo Volpi, Jacopo Cavazza, Vittorio Murino

We are interested in learning data-driven representations that can generalize well, even when trained on inherently biased data.


Intra-Camera Supervised Person Re-Identification

no code implementations12 Feb 2020 Xiangping Zhu, Xiatian Zhu, Minxian Li, Pietro Morerio, Vittorio Murino, Shaogang Gong

Existing person re-identification (re-id) methods mostly exploit a large set of cross-camera identity labelled training data.

Person Re-Identification

Generative Pseudo-label Refinement for Unsupervised Domain Adaptation

1 code implementation9 Jan 2020 Pietro Morerio, Riccardo Volpi, Ruggero Ragonesi, Vittorio Murino

We exploit this finding in an iterative procedure where a generative model and a classifier are jointly trained: in turn, the generator allows to sample cleaner data from the target distribution, and the classifier allows to associate better labels to target samples, progressively refining target pseudo-labels.

Pseudo Label Unsupervised Domain Adaptation

DMCL: Distillation Multiple Choice Learning for Multimodal Action Recognition

1 code implementation23 Dec 2019 Nuno C. Garcia, Sarah Adel Bargal, Vitaly Ablavsky, Pietro Morerio, Vittorio Murino, Stan Sclaroff

In this work, we address the problem of learning an ensemble of specialist networks using multimodal data, while considering the realistic and challenging scenario of possible missing modalities at test time.

Action Recognition Multiple-choice +1

Aggregation Signature for Small Object Tracking

no code implementations24 Oct 2019 Chunlei Liu, Wenrui Ding, Jinyu Yang, Vittorio Murino, Baochang Zhang, Jungong Han, Guodong Guo

In this paper, we propose a novel aggregation signature suitable for small object tracking, especially aiming for the challenge of sudden and large drift.

Object Tracking

Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI

no code implementations22 Oct 2019 Shahab Aslani, Vittorio Murino, Michael Dayan, Roger Tam, Diego Sona, Ghassan Hamarneh

This paper presents a simple and effective generalization method for magnetic resonance imaging (MRI) segmentation when data is collected from multiple MRI scanning sites and as a consequence is affected by (site-)domain shifts.

Lesion Segmentation MRI segmentation

Intra-Camera Supervised Person Re-Identification: A New Benchmark

no code implementations27 Aug 2019 Xiangping Zhu, Xiatian Zhu, Minxian Li, Vittorio Murino, Shaogang Gong

Existing person re-identification (re-id) methods rely mostly on a large set of inter-camera identity labelled training data, requiring a tedious data collection and annotation process therefore leading to poor scalability in practical re-id applications.

Association Multi-Label Learning +1

Unsupervised Domain-Adaptive Person Re-identification Based on Attributes

no code implementations27 Aug 2019 Xiangping Zhu, Pietro Morerio, Vittorio Murino

Training person re-identification (ReID) algorithms under the supervision of such attributes have proven to be effective in extracting local features which are important for ReID.

Domain Adaptation Domain Adaptive Person Re-Identification +2

Audio-Visual Model Distillation Using Acoustic Images

1 code implementation16 Apr 2019 Andrés F. Pérez, Valentina Sanguineti, Pietro Morerio, Vittorio Murino

In this paper, we investigate how to learn rich and robust feature representations for audio classification from visual data and acoustic images, a novel audio data modality.

Action Recognition Audio Classification +3

Cross-modal Learning by Hallucinating Missing Modalities in RGB-D Vision

1 code implementation Multimodal Scene Understanding Algorithms, Applications and Deep Learning 2019 Nuno C. Garcia, Pietro Morerio, Vittorio Murino

We report state-of-the-art or comparable results on video action recognition on the largest multimodal dataset available for this task, the NTU RGB+D, as well as on the UWA3DII and Northwestern-UCLA.

Action Recognition Multimodal Activity Recognition +2

Multi-branch Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation

no code implementations7 Nov 2018 Shahab Aslani, Michael Dayan, Loredana Storelli, Massimo Filippi, Vittorio Murino, Maria A. Rocca, Diego Sona

Our method is based on a deep end-to-end 2D convolutional neural network (CNN) for slice-based segmentation of 3D volumetric data.

Lesion Segmentation

Learning with privileged information via adversarial discriminative modality distillation

1 code implementation19 Oct 2018 Nuno C. Garcia, Pietro Morerio, Vittorio Murino

This raises the challenge of how to extract information from multimodal data in the training stage, in a form that can be exploited at test time, considering limitations such as noisy or missing modalities.

Action Recognition

Modality Distillation with Multiple Stream Networks for Action Recognition

1 code implementation ECCV 2018 Nuno Garcia, Pietro Morerio, Vittorio Murino

Particularly, we consider the case of learning representations from depth and RGB videos, while relying on RGB data only at test time.

Action Classification Action Detection +2

Generalizing to Unseen Domains via Adversarial Data Augmentation

2 code implementations NeurIPS 2018 Riccardo Volpi, Hongseok Namkoong, Ozan Sener, John Duchi, Vittorio Murino, Silvio Savarese

Only using training data from a single source distribution, we propose an iterative procedure that augments the dataset with examples from a fictitious target domain that is "hard" under the current model.

Data Augmentation Semantic Segmentation

Excitation Dropout: Encouraging Plasticity in Deep Neural Networks

1 code implementation23 May 2018 Andrea Zunino, Sarah Adel Bargal, Pietro Morerio, Jianming Zhang, Stan Sclaroff, Vittorio Murino

In this work, we utilize the evidence at each neuron to determine the probability of dropout, rather than dropping out neurons uniformly at random as in standard dropout.

Decision Making Video Recognition

Scalable and Compact 3D Action Recognition with Approximated RBF Kernel Machines

no code implementations28 Nov 2017 Jacopo Cavazza, Pietro Morerio, Vittorio Murino

Despite the recent deep learning (DL) revolution, kernel machines still remain powerful methods for action recognition.

3D Action Recognition

Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation

1 code implementation ICLR 2018 Pietro Morerio, Jacopo Cavazza, Vittorio Murino

In this work, we face the problem of unsupervised domain adaptation with a novel deep learning approach which leverages on our finding that entropy minimization is induced by the optimal alignment of second order statistics between source and target domains.

General Classification Unsupervised Domain Adaptation

Adversarial Feature Augmentation for Unsupervised Domain Adaptation

2 code implementations CVPR 2018 Riccardo Volpi, Pietro Morerio, Silvio Savarese, Vittorio Murino

Recent works showed that Generative Adversarial Networks (GANs) can be successfully applied in unsupervised domain adaptation, where, given a labeled source dataset and an unlabeled target dataset, the goal is to train powerful classifiers for the target samples.

Data Augmentation Unsupervised Domain Adaptation

Excitation Backprop for RNNs

1 code implementation CVPR 2018 Sarah Adel Bargal, Andrea Zunino, Donghyun Kim, Jianming Zhang, Vittorio Murino, Stan Sclaroff

Models are trained to caption or classify activity in videos, but little is known about the evidence used to make such decisions.

Action Recognition Temporal Action Localization +1

Dropout as a Low-Rank Regularizer for Matrix Factorization

no code implementations13 Oct 2017 Jacopo Cavazza, Pietro Morerio, Benjamin Haeffele, Connor Lane, Vittorio Murino, Rene Vidal

Regularization for matrix factorization (MF) and approximation problems has been carried out in many different ways.

An Analysis of Dropout for Matrix Factorization

no code implementations10 Oct 2017 Jacopo Cavazza, Connor Lane, Benjamin D. Haeffele, Vittorio Murino, René Vidal

While the resulting regularizer is closely related to a variational form of the nuclear norm, suggesting that dropout may limit the size of the factorization, we show that it is possible to trivially lower the objective value by doubling the size of the factorization.

Summarization and Classification of Wearable Camera Streams by Learning the Distributions Over Deep Features of Out-Of-Sample Image Sequences

no code implementations ICCV 2017 Alessandro Perina, Sadegh Mohammadi, Nebojsa Jojic, Vittorio Murino

In particular, we use constrained Markov walks over a counting grid for modeling image sequences, which not only yield good latent representations, but allow for excellent classification with only a handful of labeled training examples of the new scenes or objects, a scenario typical in lifelogging applications.

General Classification

A Compact Kernel Approximation for 3D Action Recognition

no code implementations6 Sep 2017 Jacopo Cavazza, Pietro Morerio, Vittorio Murino

In this work we reduce such complexity to be linear by proposing a novel and explicit feature map to approximate the kernel function.

3D Action Recognition

Manifold Constrained Low-Rank Decomposition

no code implementations6 Aug 2017 Chen Chen, Baochang Zhang, Alessio Del Bue, Vittorio Murino

Low-rank decomposition (LRD) is a state-of-the-art method for visual data reconstruction and modelling.

When Kernel Methods meet Feature Learning: Log-Covariance Network for Action Recognition from Skeletal Data

no code implementations3 Aug 2017 Jacopo Cavazza, Pietro Morerio, Vittorio Murino

Human action recognition from skeletal data is a hot research topic and important in many open domain applications of computer vision, thanks to recently introduced 3D sensors.

Action Recognition Temporal Action Localization

What Will I Do Next? The Intention from Motion Experiment

no code implementations3 Aug 2017 Andrea Zunino, Jacopo Cavazza, Atesh Koul, Andrea Cavallo, Cristina Becchio, Vittorio Murino

In this paper, we bridge cognitive and computer vision studies, by demonstrating the effectiveness of video-based approaches for the prediction of human intentions.

General Classification

Unsupervised Adaptive Re-identification in Open World Dynamic Camera Networks

no code implementations CVPR 2017 Rameswar Panda, Amran Bhuiyan, Vittorio Murino, Amit K. Roy-Chowdhury

Most approaches have neglected the dynamic and open world nature of the re-identification problem, where a new camera may be temporarily inserted into an existing system to get additional information.

Person Re-Identification

Correlation Alignment by Riemannian Metric for Domain Adaptation

1 code implementation23 May 2017 Pietro Morerio, Vittorio Murino

Domain adaptation techniques address the problem of reducing the sensitivity of machine learning methods to the so-called domain shift, namely the difference between source (training) and target (test) data distributions.

Unsupervised Domain Adaptation

Curriculum Dropout

2 code implementations ICCV 2017 Pietro Morerio, Jacopo Cavazza, Riccardo Volpi, Rene Vidal, Vittorio Murino

This induces an adaptive regularization scheme that smoothly increases the difficulty of the optimization problem.

Image Classification Scheduling

Modeling Retinal Ganglion Cell Population Activity with Restricted Boltzmann Machines

no code implementations11 Jan 2017 Matteo Zanotto, Riccardo Volpi, Alessandro Maccione, Luca Berdondini, Diego Sona, Vittorio Murino

The idea was to figure out if binary latent states encode the regularities associated to different visual stimuli, as modes in the joint distribution.

Kernel Methods on Approximate Infinite-Dimensional Covariance Operators for Image Classification

no code implementations29 Sep 2016 Hà Quang Minh, Marco San Biagio, Loris Bazzani, Vittorio Murino

This paper presents a novel framework for visual object recognition using infinite-dimensional covariance operators of input features in the paradigm of kernel methods on infinite-dimensional Riemannian manifolds.

General Classification Image Classification +1

Active Regression with Adaptive Huber Loss

no code implementations5 Jun 2016 Jacopo Cavazza, Vittorio Murino

This paper addresses the scalar regression problem through a novel solution to exactly optimize the Huber loss in a general semi-supervised setting, which combines multi-view learning and manifold regularization.


Approximate Log-Hilbert-Schmidt Distances Between Covariance Operators for Image Classification

no code implementations CVPR 2016 Ha Quang Minh, Marco San Biagio, Loris Bazzani, Vittorio Murino

This paper presents a novel framework for visual object recognition using infinite-dimensional covariance operators of input features, in the paradigm of kernel methods on infinite-dimensional Riemannian manifolds.

General Classification Image Classification +1

Revisiting Human Action Recognition: Personalization vs. Generalization

no code implementations2 May 2016 Andrea Zunino, Jacopo Cavazza, Vittorio Murino

In particular, considering that each human action in the datasets is performed several times by different subjects, we were able to precisely quantify the effect of inter- and intra-subject variability, so as to figure out the impact of several learning approaches in terms of classification performance.

Action Classification Action Recognition +2

Kernelized Covariance for Action Recognition

no code implementations22 Apr 2016 Jacopo Cavazza, Andrea Zunino, Marco San Biagio, Vittorio Murino

In this paper we aim at increasing the descriptive power of the covariance matrix, limited in capturing linear mutual dependencies between variables only.

3D Action Recognition

Action Recognition with Image Based CNN Features

no code implementations13 Dec 2015 Mahdyar Ravanbakhsh, Hossein Mousavi, Mohammad Rastegari, Vittorio Murino, Larry S. Davis

Action recognition tasks usually relies on complex handcrafted structures as features to represent the human action model.

Action Recognition Temporal Action Localization

Learning With Dataset Bias in Latent Subcategory Models

no code implementations CVPR 2015 Dimitris Stamos, Samuele Martelli, Moin Nabi, Andrew McDonald, Vittorio Murino, Massimiliano Pontil

However, previous work has highlighted the possible danger of simply training a model from the combined datasets, due to the presence of bias.

3D Pose from Detections

no code implementations17 Feb 2015 Cosimo Rubino, Marco Crocco, Alessandro Perina, Vittorio Murino, Alessio Del Bue

We present a novel method to infer, in closed-form, a general 3D spatial occupancy and orientation of a collection of rigid objects given 2D image detections from a sequence of images.

Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces

no code implementations NeurIPS 2014 Minh Ha Quang, Marco San Biagio, Vittorio Murino

This paper introduces a novel mathematical and computational framework, namely {\it Log-Hilbert-Schmidt metric} between positive definite operators on a Hilbert space.

Image Classification

Audio Surveillance: a Systematic Review

no code implementations27 Sep 2014 Marco Crocco, Marco Cristani, Andrea Trucco, Vittorio Murino

Despite surveillance systems are becoming increasingly ubiquitous in our living environment, automated surveillance, currently based on video sensory modality and machine intelligence, lacks most of the time the robustness and reliability required in several real applications.

Object Tracking

A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-Regularized Multi-view Learning

no code implementations31 Jan 2014 Ha Quang Minh, Loris Bazzani, Vittorio Murino

This paper presents a general vector-valued reproducing kernel Hilbert spaces (RKHS) framework for the problem of learning an unknown functional dependency between a structured input space and a structured output space.

MULTI-VIEW LEARNING Object Recognition

Structural epitome: a way to summarize one’s visual experience

no code implementations NeurIPS 2010 Nebojsa Jojic, Alessandro Perina, Vittorio Murino

In order to study the properties of total visual input in humans, a single subject wore a camera for two weeks capturing, on average, an image every 20 seconds (www. research. microsoft. com/~jojic/aihs).

Free energy score space

no code implementations NeurIPS 2009 Alessandro Perina, Marco Cristani, Umberto Castellani, Vittorio Murino, Nebojsa Jojic

Score functions induced by generative models extract fixed-dimension feature vectors from different-length data observations by subsuming the process of data generation, projecting them in highly informative spaces called score spaces.

General Classification

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