1 code implementation • 17 Apr 2024 • Luca Scofano, Alessio Sampieri, Tommaso Campari, Valentino Sacco, Indro Spinelli, Lamberto Ballan, Fabio Galasso
We propose the first Social Dynamics Adaptation model (SDA) based on the robot's state-action history to infer the social dynamics.
1 code implementation • 18 May 2023 • Davide Rigoni, Luca Parolari, Luciano Serafini, Alessandro Sperduti, Lamberto Ballan
The first untrained module aims to return a rough alignment between textual phrases and bounding boxes.
no code implementations • 15 May 2023 • Sourav Das, Guglielmo Camporese, Shaokang Cheng, Lamberto Ballan
Long-term trajectory forecasting is an important and challenging problem in the fields of computer vision, machine learning, and robotics.
no code implementations • ICCV 2023 • Enrico Cancelli, Tommaso Campari, Luciano Serafini, Angel X. Chang, Lamberto Ballan
In this paper, we propose an end-to-end architecture that exploits Proximity-Aware Tasks (referred as to Risk and Proximity Compass) to inject into a reinforcement learning navigation policy the ability to infer common-sense social behaviors.
1 code implementation • 26 Oct 2022 • Nada Osman, Guglielmo Camporese, Lamberto Ballan
Human intention prediction is a growing area of research where an activity in a video has to be anticipated by a vision-based system.
2 code implementations • 1 Jun 2022 • Guglielmo Camporese, Elena Izzo, Lamberto Ballan
Vision Transformers (ViTs) enabled the use of the transformer architecture on vision tasks showing impressive performances when trained on big datasets.
1 code implementation • 25 Apr 2022 • Luigi Filippo Chiara, Pasquale Coscia, Sourav Das, Simone Calderara, Rita Cucchiara, Lamberto Ballan
Human trajectory forecasting is a key component of autonomous vehicles, social-aware robots and advanced video-surveillance applications.
no code implementations • CVPR 2022 • Alessio Monti, Angelo Porrello, Simone Calderara, Pasquale Coscia, Lamberto Ballan, Rita Cucchiara
To this end, we conceive a novel distillation strategy that allows a knowledge transfer from a teacher network to a student one, the latter fed with fewer observations (just two ones).
no code implementations • CVPR 2022 • Tommaso Campari, Leonardo Lamanna, Paolo Traverso, Luciano Serafini, Lamberto Ballan
In this paper, we present a novel approach to incrementally learn an Abstract Model of an unknown environment, and show how an agent can reuse the learned model for tackling the Object Goal Navigation task.
no code implementations • 2 Sep 2021 • Nada Osman, Guglielmo Camporese, Pasquale Coscia, Lamberto Ballan
Action anticipation in egocentric videos is a difficult task due to the inherently multi-modal nature of human actions.
1 code implementation • ICCV 2021 • Yunrui Guo, Guglielmo Camporese, Wenjing Yang, Alessandro Sperduti, Lamberto Ballan
In this way, we are able to control the compactness of the features of the same class around the center of the gaussians, thus controlling the ability of the classifier in detecting samples from unknown classes.
no code implementations • 2 Apr 2021 • Dennis Núñez-Fernández, Lamberto Ballan, Gabriel Jiménez-Avalos, Jorge Coronel, Patricia Sheen, Mirko Zimic
One of the most serious public health problems in Peru and worldwide is Tuberculosis (TB), which is produced by a bacterium known as Mycobacterium tuberculosis.
no code implementations • 21 Aug 2020 • Tommaso Campari, Paolo Eccher, Luciano Serafini, Lamberto Ballan
We study this question in the context of Object Navigation, a problem in which an agent has to reach an object of a specific class while moving in a complex domestic environment.
no code implementations • 6 Jul 2020 • Dennis Núñez-Fernández, Lamberto Ballan, Gabriel Jiménez-Avalos, Jorge Coronel, Mirko Zimic
Tuberculosis (TB), caused by a germ called Mycobacterium tuberculosis, is one of the most serious public health problems in Peru and the world.
no code implementations • 5 Jul 2020 • Dennis Núñez-Fernández, Lamberto Ballan, Gabriel Jiménez-Avalos, Jorge Coronel, Mirko Zimic
Tuberculosis, caused by a bacteria called Mycobacterium tuberculosis, is one of the most serious public health problems worldwide.
1 code implementation • 17 May 2020 • Alessia Bertugli, Simone Calderara, Pasquale Coscia, Lamberto Ballan, Rita Cucchiara
Anticipating human motion in crowded scenarios is essential for developing intelligent transportation systems, social-aware robots and advanced video surveillance applications.
no code implementations • 16 Apr 2020 • Guglielmo Camporese, Pasquale Coscia, Antonino Furnari, Giovanni Maria Farinella, Lamberto Ballan
Since multiple actions may equally occur in the future, we treat action anticipation as a multi-label problem with missing labels extending the concept of label smoothing.
no code implementations • 13 Oct 2019 • Tobia Tesan, Pasquale Coscia, Lamberto Ballan
Images represent a commonly used form of visual communication among people.
1 code implementation • 19 Sep 2019 • Matteo Lisotto, Pasquale Coscia, Lamberto Ballan
Mimicking human ability to forecast future positions or interpret complex interactions in urban scenarios, such as streets, shopping malls or squares, is essential to develop socially compliant robots or self-driving cars.
no code implementations • 14 Jun 2017 • Christian Rupprecht, Ansh Kapil, Nan Liu, Lamberto Ballan, Federico Tombari
One of the main problems in webly-supervised learning is cleaning the noisy labeled data from the web.
no code implementations • 6 May 2017 • Federico Bartoli, Giuseppe Lisanti, Lamberto Ballan, Alberto del Bimbo
To this end, we propose a "context-aware" recurrent neural network LSTM model, which can learn and predict human motion in crowded spaces such as a sidewalk, a museum or a shopping mall.
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 • 16 May 2016 • Tiberio Uricchio, Lamberto Ballan, Lorenzo Seidenari, Alberto del Bimbo
Automatic image annotation is among the fundamental problems in computer vision and pattern recognition, and it is becoming increasingly important in order to develop algorithms that are able to search and browse large-scale image collections.
no code implementations • 22 Mar 2016 • Lamberto Ballan, Francesco Castaldo, Alexandre Alahi, Francesco Palmieri, Silvio Savarese
When given a single frame of the video, humans can not only interpret the content of the scene, but also they are able to forecast the near future.
no code implementations • ICCV 2015 • Justin Johnson, Lamberto Ballan, Fei-Fei Li
Some images that are difficult to recognize on their own may become more clear in the context of a neighborhood of related images with similar social-network metadata.
1 code implementation • 28 Mar 2015 • Xirong Li, Tiberio Uricchio, Lamberto Ballan, Marco Bertini, Cees G. M. Snoek, Alberto del Bimbo
Where previous reviews on content-based image retrieval emphasize on what can be seen in an image to bridge the semantic gap, this survey considers what people tag about an image.
no code implementations • 2 Jul 2014 • Lamberto Ballan, Marco Bertini, Giuseppe Serra, Alberto del Bimbo
Our approach exploits collective knowledge embedded in user-generated tags and web sources, and visual similarity of keyframes and images uploaded to social sites like YouTube and Flickr, as well as web sources like Google and Bing.