Search Results for author: Marco Cristani

Found 38 papers, 16 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

Split-Et-Impera: A Framework for the Design of Distributed Deep Learning Applications

1 code implementation22 Mar 2023 Luigi Capogrosso, Federico Cunico, Michele Lora, Marco Cristani, Franco Fummi, Davide Quaglia

Many recent pattern recognition applications rely on complex distributed architectures in which sensing and computational nodes interact together through a communication network.

A Masked Face Classification Benchmark

1 code implementation23 Nov 2022 Federico Cunico, Andrea Toaiari, Marco Cristani

Results show that the richness of SF-MASK (real + synthetic images) leads all of the tested classifiers to perform better than exploiting comparative face mask datasets, on a fixed 1077 images testing set.

Classification Multi-class Classification

On the use of learning-based forecasting methods for ameliorating fashion business processes: A position paper

no code implementations9 Nov 2022 Geri Skenderi, Christian Joppi, Matteo Denitto, Marco Cristani

The fashion industry is one of the most active and competitive markets in the world, manufacturing millions of products and reaching large audiences every year.

Management Marketing

Leveraging commonsense for object localisation in partial scenes

no code implementations1 Nov 2022 Francesco Giuliari, Geri Skenderi, Marco Cristani, Alessio Del Bue, Yiming Wang

With the proposed graph-based scene representation, we estimate the unknown position of the target object using a Graph Neural Network that implements a novel attentional message passing mechanism.

I-SPLIT: Deep Network Interpretability for Split Computing

1 code implementation23 Sep 2022 Federico Cunico, Luigi Capogrosso, Francesco Setti, Damiano Carra, Franco Fummi, Marco Cristani

A neuron is important if its gradient with respect to the correct class decision is high.

Toward Smart Doors: A Position Paper

no code implementations23 Sep 2022 Luigi Capogrosso, Geri Skenderi, Federico Girella, Franco Fummi, Marco Cristani

In particular, a smart door system predicts the intention of people near the door based on the social context of the surrounding environment and then makes rational decisions about whether or not to open the door.

Pose Forecasting in Industrial Human-Robot Collaboration

1 code implementation24 Jul 2022 Alessio Sampieri, Guido D'Amely, Andrea Avogaro, Federico Cunico, Geri Skenderi, Francesco Setti, Marco Cristani, Fabio Galasso

Pushing back the frontiers of collaborative robots in industrial environments, we propose a new Separable-Sparse Graph Convolutional Network (SeS-GCN) for pose forecasting.

Human Pose Forecasting

POP: Mining POtential Performance of new fashion products via webly cross-modal query expansion

1 code implementation22 Jul 2022 Christian Joppi, Geri Skenderi, Marco Cristani

We propose a data-centric pipeline able to generate exogenous observation data for the New Fashion Product Performance Forecasting (NFPPF) problem, i. e., predicting the performance of a brand-new clothing probe with no available past observations.

New Product Sales Forecasting Time Series Analysis

SHREC 2022 Track on Online Detection of Heterogeneous Gestures

no code implementations14 Jul 2022 Ariel Caputo, Marco Emporio, Andrea Giachetti, Marco Cristani, Guido Borghi, Andrea D'Eusanio, Minh-Quan Le, Hai-Dang Nguyen, Minh-Triet Tran, F. Ambellan, M. Hanik, E. Nava-Yazdani, C. von Tycowicz

This paper presents the outcomes of a contest organized to evaluate methods for the online recognition of heterogeneous gestures from sequences of 3D hand poses.

Mixed Reality

Under the Hood of Transformer Networks for Trajectory Forecasting

no code implementations22 Mar 2022 Luca Franco, Leonardo Placidi, Francesco Giuliari, Irtiza Hasan, Marco Cristani, Fabio Galasso

This paper proposes the first in-depth study of Transformer Networks (TF) and Bidirectional Transformers (BERT) for the forecasting of the individual motion of people, without bells and whistles.

Trajectory Forecasting

Spatial Commonsense Graph for Object Localisation in Partial Scenes

1 code implementation CVPR 2022 Francesco Giuliari, Geri Skenderi, Marco Cristani, Yiming Wang, Alessio Del Bue

The SCG is used to estimate the unknown position of the target object in two steps: first, we feed the SCG into a novel Proximity Prediction Network, a graph neural network that uses attention to perform distance prediction between the node representing the target object and the nodes representing the observed objects in the SCG; second, we propose a Localisation Module based on circular intersection to estimate the object position using all the predicted pairwise distances in order to be independent of any reference system.

MovingFashion: a Benchmark for the Video-to-Shop Challenge

1 code implementation6 Oct 2021 Marco Godi, Christian Joppi, Geri Skenderi, Marco Cristani

Retrieving clothes which are worn in social media videos (Instagram, TikTok) is the latest frontier of e-fashion, referred to as "video-to-shop" in the computer vision literature.


Well Googled is Half Done: Multimodal Forecasting of New Fashion Product Sales with Image-based Google Trends

1 code implementation20 Sep 2021 Geri Skenderi, Christian Joppi, Matteo Denitto, Marco Cristani

In particular, we propose a neural network-based approach, where an encoder learns a representation of the exogenous time series, while the decoder forecasts the sales based on the Google Trends encoding and the available visual and metadata information.

New Product Sales Forecasting Time Series Analysis

Infinite Feature Selection: A Graph-based Feature Filtering Approach

1 code implementation15 Jun 2020 Giorgio Roffo, Simone Melzi, Umberto Castellani, Alessandro Vinciarelli, Marco Cristani

We propose a filtering feature selection framework that considers subsets of features as paths in a graph, where a node is a feature and an edge indicates pairwise (customizable) relations among features, dealing with relevance and redundancy principles.

feature selection

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).

An integrated light management system with real-time light measurement and human perception

no code implementations17 Apr 2020 Theodore Tsesmelis, Irtiza Hasan, Marco Cristani, Alessio Del Bue, Fabio Galasso

Illumination is important for well-being, productivity and safety across several environments, including offices, retail shops and industrial warehouses.


Transformer Networks for Trajectory Forecasting

1 code implementation18 Mar 2020 Francesco Giuliari, Irtiza Hasan, Marco Cristani, Fabio Galasso

In particular, the TF model without bells and whistles yields the best score on the largest and most challenging trajectory forecasting benchmark of TrajNet.

Trajectory Forecasting

Texel-Att: Representing and Classifying Element-based Textures by Attributes

1 code implementation29 Aug 2019 Marco Godi, Christian Joppi, Andrea Giachetti, Fabio Pellacini, Marco Cristani

It first individuates texels, characterizing them with individual attributes; subsequently, texels are grouped and characterized through layout attributes, which give the Texel-Att representation.

Texture Retrieval in the Wild through detection-based attributes

no code implementations29 Aug 2019 Christian Joppi, Marco Godi, Andrea Giachetti, Fabio Pellacini, Marco Cristani

Capturing the essence of a textile image in a robust way is important to retrieve it in a large repository, especially if it has been acquired in the wild (by taking a photo of the textile of interest).


Human-centric light sensing and estimation from RGBD images: The invisible light switch

no code implementations30 Jan 2019 Theodore Tsesmelis, Irtiza Hasan, Marco Cristani, Alessio Del Bue, Fabio Galasso

ILS may therefore dim those luminaires, which are not seen by the user, resulting in an effective energy saving, especially in large open offices (where light may otherwise be ON everywhere for a single person).

RGBD2lux: Dense light intensity estimation with an RGBD sensor

no code implementations20 Sep 2018 Theodore Tsesmelis, Irtiza Hasan, Marco Cristani, Fabio Galasso, Alessio Del Bue

The proposed method uses both depth data and images from the sensor to provide a dense measure of light intensity in the field of view of the camera.

MX-LSTM: mixing tracklets and vislets to jointly forecast trajectories and head poses

no code implementations CVPR 2018 Irtiza Hasan, Francesco Setti, Theodore Tsesmelis, Alessio Del Bue, Fabio Galasso, Marco Cristani

Recent approaches on trajectory forecasting use tracklets to predict the future positions of pedestrians exploiting Long Short Term Memory (LSTM) architectures.

Trajectory Forecasting

Understanding Deep Architectures by Visual Summaries

2 code implementations27 Jan 2018 Marco Carletti, Marco Godi, Maedeh Aghaei, Francesco Giuliari, Marco Cristani

In deep learning, visualization techniques extract the salient patterns exploited by deep networks for image classification, focusing on single images; no effort has been spent in investigating whether these patterns are systematically related to precise semantic entities over multiple images belonging to a same class, thus failing to capture the very understanding of the image class the network has realized.

General Classification Image Classification

What your Facebook Profile Picture Reveals about your Personality

no code implementations3 Aug 2017 Cristina Segalin, Fabio Celli, Luca Polonio, Michal Kosinski, David Stillwell, Nicu Sebe, Marco Cristani, Bruno Lepri

We analyze the effectiveness of four families of visual features and we discuss some human interpretable patterns that explain the personality traits of the individuals.

General Classification

Looking Beyond Appearances: Synthetic Training Data for Deep CNNs in Re-identification

no code implementations11 Jan 2017 Igor Barros Barbosa, Marco Cristani, Barbara Caputo, Aleksander Rognhaugen, Theoharis Theoharis

Re-identification is generally carried out by encoding the appearance of a subject in terms of outfit, suggesting scenarios where people do not change their attire.

Infinite Feature Selection

1 code implementation ICCV 2015 Giorgio Roffo, Simone Melzi, Marco Cristani

Filter-based feature selection has become crucial in many classification settings, especially object recognition, recently faced with feature learning strategies that originate thousands of cues.

Classification feature selection +2

The S-Hock Dataset: Analyzing Crowds at the Stadium

no code implementations CVPR 2015 Davide Conigliaro, Paolo Rota, Francesco Setti, Chiara Bassetti, Nicola Conci, Nicu Sebe, Marco Cristani

In the dataset, a massive annotation has been carried out, focusing on the spectators at different levels of details: at a higher level, people have been labeled depending on the team they are supporting and the fact that they know the people close to them; going to the lower levels, standard pose information has been considered (regarding the head, the body) but also fine grained actions such as hands on hips, clapping hands etc.

Head Pose Estimation Sociology

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

F-formation Detection: Individuating Free-standing Conversational Groups in Images

no code implementations9 Sep 2014 Francesco Setti, Chris Russell, Chiara Bassetti, Marco Cristani

Then, as a main contribution, we present a brand new method for the automatic detection of groups in still images, which is based on a graph-cuts framework for clustering individuals; in particular we are able to codify in a computational sense the sociological definition of F-formation, that is very useful to encode a group having only proxemic information: position and orientation of people.


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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