Search Results for author: Federico Becattini

Found 14 papers, 2 papers with code

Forecasting Future Instance Segmentation with Learned Optical Flow and Warping

no code implementations15 Nov 2022 Andrea Ciamarra, Federico Becattini, Lorenzo Seidenari, Alberto del Bimbo

For an autonomous vehicle it is essential to observe the ongoing dynamics of a scene and consequently predict imminent future scenarios to ensure safety to itself and others.

Instance Segmentation Optical Flow Estimation +1

Fashion Recommendation Based on Style and Social Events

no code implementations1 Aug 2022 Federico Becattini, Lavinia De Divitiis, Claudio Baecchi, Alberto del Bimbo

Overall, we integrate in a state of the art garment recommendation framework a style classifier and an event classifier in order to condition recommendation on a given query.

Is GPT-3 all you need for Visual Question Answering in Cultural Heritage?

no code implementations25 Jul 2022 Pietro Bongini, Federico Becattini, Alberto del Bimbo

The use of Deep Learning and Computer Vision in the Cultural Heritage domain is becoming highly relevant in the last few years with lots of applications about audio smart guides, interactive museums and augmented reality.

Question Answering Visual Question Answering

Online Deep Clustering with Video Track Consistency

no code implementations7 Jun 2022 Alessandra Alfani, Federico Becattini, Lorenzo Seidenari, Alberto del Bimbo

Several unsupervised and self-supervised approaches have been developed in recent years to learn visual features from large-scale unlabeled datasets.

Deep Clustering

SMEMO: Social Memory for Trajectory Forecasting

no code implementations23 Mar 2022 Francesco Marchetti, Federico Becattini, Lorenzo Seidenari, Alberto del Bimbo

Effective modeling of human interactions is of utmost importance when forecasting behaviors such as future trajectories.

Trajectory Forecasting

Garment Recommendation with Memory Augmented Neural Networks

no code implementations11 Dec 2020 Lavinia De Divitiis, Federico Becattini, Claudio Baecchi, Alberto del Bimbo

In particular, we aim at retrieving a variety of modalities in which a certain garment can be combined.

Recommendation Systems

Temporal Binary Representation for Event-Based Action Recognition

1 code implementation18 Oct 2020 Simone Undri Innocenti, Federico Becattini, Federico Pernici, Alberto del Bimbo

In this paper we present an event aggregation strategy to convert the output of an event camera into frames processable by traditional Computer Vision algorithms.

 Ranked #1 on Gesture Recognition on DVS128 Gesture (using extra training data)

Action Recognition Gesture Recognition

Explaining Autonomous Driving by Learning End-to-End Visual Attention

no code implementations5 Jun 2020 Luca Cultrera, Lorenzo Seidenari, Federico Becattini, Pietro Pala, Alberto del Bimbo

Current deep learning based autonomous driving approaches yield impressive results also leading to in-production deployment in certain controlled scenarios.

Autonomous Driving Imitation Learning

Visual Question Answering for Cultural Heritage

no code implementations22 Mar 2020 Pietro Bongini, Federico Becattini, Andrew D. Bagdanov, Alberto del Bimbo

This will turn the classic audio guide into a smart personal instructor with which the visitor can interact by asking for explanations focused on specific interests.

Question Answering Visual Question Answering +1

Semantic Road Layout Understanding by Generative Adversarial Inpainting

no code implementations29 May 2018 Lorenzo Berlincioni, Federico Becattini, Leonardo Galteri, Lorenzo Seidenari, Alberto del Bimbo

Autonomous driving is becoming a reality, yet vehicles still need to rely on complex sensor fusion to understand the scene they act in.

Autonomous Driving Semantic Segmentation

Segmentation Free Object Discovery in Video

no code implementations1 Sep 2016 Giovanni Cuffaro, Federico Becattini, Claudio Baecchi, Lorenzo Seidenari, Alberto del Bimbo

In this paper we present a simple yet effective approach to extend without supervision any object proposal from static images to videos.

Object Discovery

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