no code implementations • 18 Feb 2024 • Federico Becattini, Xiaolin Chen, Andrea Puccia, Haokun Wen, Xuemeng Song, Liqiang Nie, Alberto del Bimbo
Recommending fashion items often leverages rich user profiles and makes targeted suggestions based on past history and previous purchases.
no code implementations • 18 Feb 2024 • Federico Becattini, Lorenzo Berlincioni, Luca Cultrera, Alberto del Bimbo
Neuromorphic sensors, also known as event cameras, are a class of imaging devices mimicking the function of biological visual systems.
no code implementations • 29 Jan 2024 • Lorenzo Berlincioni, Luca Cultrera, Federico Becattini, Alberto del Bimbo
Recognizing faces and their underlying emotions is an important aspect of biometrics.
no code implementations • 31 Oct 2023 • Andrea Ciamarra, Federico Becattini, Lorenzo Seidenari, Alberto del Bimbo
We train the proposed model to also perform predictions for several timesteps in the future.
no code implementations • 31 Oct 2023 • Andrea Ciamarra, Roberto Caldelli, Federico Becattini, Lorenzo Seidenari, Alberto del Bimbo
In particular, when an image (video) is captured the overall geometry of the scene (e. g. surfaces) and the acquisition process (e. g. illumination) determine a univocal environment that is directly represented by the image pixel values; all these intrinsic relations are possibly changed by the deepfake generation process.
no code implementations • 31 Oct 2023 • Luca Cultrera, Federico Becattini, Lorenzo Seidenari, Pietro Pala, Alberto del Bimbo
We feed the state of the vehicle along with the representation of the environment as a special token of the transformer and propagate it throughout the network.
no code implementations • 24 Aug 2023 • Alessandro Simoni, Francesco Marchetti, Guido Borghi, Federico Becattini, Lorenzo Seidenari, Roberto Vezzani, Alberto del Bimbo
Technologies to enable safe and effective collaboration and coexistence between humans and robots have gained significant importance in the last few years.
1 code implementation • 14 Aug 2023 • Dario Cioni, Lorenzo Berlincioni, Federico Becattini, Alberto del Bimbo
Cultural heritage applications and advanced machine learning models are creating a fruitful synergy to provide effective and accessible ways of interacting with artworks.
no code implementations • 26 Jul 2023 • Lorenzo Agnolucci, Alberto Baldrati, Francesco Todino, Federico Becattini, Marco Bertini, Alberto del Bimbo
Among these, the CLIP model has shown remarkable capabilities for zero-shot transfer by matching an image and a custom textual prompt in its latent space.
no code implementations • 17 Apr 2023 • Federico Becattini, Federico Maria Teotini, Alberto del Bimbo
We attempt to bridge the gap between outfit recommendation and generation by leveraging a graph-based representation of items in a collection.
1 code implementation • 13 Apr 2023 • Lorenzo Berlincioni, Luca Cultrera, Chiara Albisani, Lisa Cresti, Andrea Leonardo, Sara Picchioni, Federico Becattini, Alberto del Bimbo
Recently, event cameras have shown large applicability in several computer vision fields especially concerning tasks that require high temporal resolution.
no code implementations • 15 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.
1 code implementation • 1 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.
no code implementations • 25 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.
no code implementations • 7 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.
no code implementations • 23 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.
Ranked #5 on Trajectory Prediction on Stanford Drone
no code implementations • 11 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.
1 code implementation • 18 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 #4 on Gesture Recognition on DVS128 Gesture (using extra training data)
no code implementations • 18 Oct 2020 • Lorenzo Berlincioni, Federico Becattini, Lorenzo Seidenari, Alberto del Bimbo
Trajectory prediction is an important task, especially in autonomous driving.
1 code implementation • CVPR 2020 • Francesco Marchetti, Federico Becattini, Lorenzo Seidenari, Alberto del Bimbo
Autonomous vehicles are expected to drive in complex scenarios with several independent non cooperating agents.
no code implementations • 5 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.
no code implementations • 22 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.
no code implementations • 29 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.
1 code implementation • 4 May 2017 • Federico Becattini, Tiberio Uricchio, Lorenzo Seidenari, Lamberto Ballan, Alberto del Bimbo
In this paper we deal with the problem of predicting action progress in videos.
no code implementations • 1 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.