Search Results for author: Lamberto Ballan

Found 24 papers, 7 papers with code

Exploiting Socially-Aware Tasks for Embodied Social Navigation

no code implementations1 Dec 2022 Enrico Cancelli, Tommaso Campari, Luciano Serafini, Angel X. Chang, Lamberto Ballan

In this paper, we propose an end-to-end architecture that exploits Socially-Aware Tasks (referred as to Risk and Social Compass) to inject into a reinforcement learning navigation policy the ability to infer common-sense social behaviors.

Common Sense Reasoning Navigate

TAMFormer: Multi-Modal Transformer with Learned Attention Mask for Early Intent Prediction

1 code implementation26 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.

Where are my Neighbors? Exploiting Patches Relations in Self-Supervised Vision Transformer

1 code implementation1 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.

Inductive Bias Self-Supervised Learning

Goal-driven Self-Attentive Recurrent Networks for Trajectory Prediction

1 code implementation25 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.

Autonomous Vehicles Trajectory Forecasting

How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting

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).

Knowledge Distillation Trajectory Forecasting +1

Online Learning of Reusable Abstract Models for Object Goal Navigation

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.

Image Segmentation online learning +1

Conditional Variational Capsule Network for Open Set Recognition

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.

Open Set Learning

Prediction of Tuberculosis using U-Net and segmentation techniques

no code implementations2 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.

Exploiting Scene-specific Features for Object Goal Navigation

no code implementations21 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.

Visual Navigation

Automatic semantic segmentation for prediction of tuberculosis using lens-free microscopy images

no code implementations6 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.

Semantic Segmentation

Using Capsule Neural Network to predict Tuberculosis in lens-free microscopic images

no code implementations5 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.

AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction

1 code implementation17 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.

Graph Attention Multi-future Trajectory Prediction +2

Knowledge Distillation for Action Anticipation via Label Smoothing

no code implementations16 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.

Action Anticipation Autonomous Driving +1

Social and Scene-Aware Trajectory Prediction in Crowded Spaces

1 code implementation19 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.

Self-Driving Cars Trajectory Prediction

Context-Aware Trajectory Prediction

no code implementations6 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.

Navigate Trajectory Prediction

Automatic Image Annotation via Label Transfer in the Semantic Space

no code implementations16 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.

Denoising

Knowledge Transfer for Scene-specific Motion Prediction

no code implementations22 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.

motion prediction Trajectory Prediction +1

Love Thy Neighbors: Image Annotation by Exploiting Image Metadata

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.

Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval

1 code implementation28 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.

Content-Based Image Retrieval Retrieval +1

A Data-Driven Approach for Tag Refinement and Localization in Web Videos

no code implementations2 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.

TAG

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