122 citations · 328 across the 22 of their papers we have counts for
28 papers
From Detection to Localization: A Unified Forensics Framework for Fully Synthetic and Tampered Images
Annalisa Gallina, Marco Fiorucci, Marco Brigo +2
The rapid advancement of generative models has significantly worsened the problem of manipulated image detection, as these methods are capable of producing highly realistic forgeri…
Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement
Davide Rigoni, Luca Parolari, Luciano Serafini +2
Using only image-sentence pairs, weakly-supervised visual-textual grounding aims to learn region-phrase correspondences of the respective entity mentions. Compared to the supervise…
Distilling Knowledge for Short-to-Long Term Trajectory Prediction
Sourav Das, Guglielmo Camporese, Shaokang Cheng +1
Long-term trajectory forecasting is an important and challenging problem in the fields of computer vision, machine learning, and robotics. One fundamental difficulty stands in the…
Exploiting Proximity-Aware Tasks for Embodied Social Navigation
Enrico Cancelli, Tommaso Campari, Luciano Serafini +2
Learning how to navigate among humans in an occluded and spatially constrained indoor environment, is a key ability required to embodied agent to be integrated into our society. In…
TAMFormer: Multi-Modal Transformer with Learned Attention Mask for Early Intent Prediction
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. To this end, the model creates a representatio…
Where are my Neighbors? Exploiting Patches Relations in Self-Supervised Vision Transformer
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. However, on relatively smal…
Goal-driven Self-Attentive Recurrent Networks for Trajectory Prediction
Luigi Filippo Chiara, Pasquale Coscia, Sourav Das +3
Human trajectory forecasting is a key component of autonomous vehicles, social-aware robots and advanced video-surveillance applications. This challenging task typically requires k…
How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting
Alessio Monti, Angelo Porrello, Simone Calderara +3
Accurate prediction of future human positions is an essential task for modern video-surveillance systems. Current state-of-the-art models usually rely on a "history" of past tracke…
Online Learning of Reusable Abstract Models for Object Goal Navigation
Tommaso Campari, Leonardo Lamanna, Paolo Traverso +2
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 Ob…
SlowFast Rolling-Unrolling LSTMs for Action Anticipation in Egocentric Videos
Nada Osman, Guglielmo Camporese, Pasquale Coscia +1
Action anticipation in egocentric videos is a difficult task due to the inherently multi-modal nature of human actions. Additionally, some actions happen faster or slower than othe…
Prediction of Tuberculosis using U-Net and segmentation techniques
Dennis Núñez-Fernández, Lamberto Ballan, Gabriel Jiménez-Avalos +3
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. The purpose of this…
Conditional Variational Capsule Network for Open Set Recognition
Yunrui Guo, Guglielmo Camporese, Wenjing Yang +2
In open set recognition, a classifier has to detect unknown classes that are not known at training time. In order to recognize new categories, the classifier has to project the inp…
Exploiting Scene-specific Features for Object Goal Navigation
Tommaso Campari, Paolo Eccher, Luciano Serafini +1
Can the intrinsic relation between an object and the room in which it is usually located help agents in the Visual Navigation Task? We study this question in the context of Object…
Automatic semantic segmentation for prediction of tuberculosis using lens-free microscopy images
Dennis Núñez-Fernández, Lamberto Ballan, Gabriel Jiménez-Avalos +2
Tuberculosis (TB), caused by a germ called Mycobacterium tuberculosis, is one of the most serious public health problems in Peru and the world. The development of this project seek…
Using Capsule Neural Network to predict Tuberculosis in lens-free microscopic images
Dennis Núñez-Fernández, Lamberto Ballan, Gabriel Jiménez-Avalos +2
Tuberculosis, caused by a bacteria called Mycobacterium tuberculosis, is one of the most serious public health problems worldwide. This work seeks to facilitate and automate the pr…
AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction
Alessia Bertugli, Simone Calderara, Pasquale Coscia +2
Anticipating human motion in crowded scenarios is essential for developing intelligent transportation systems, social-aware robots and advanced video surveillance applications. A k…
Knowledge Distillation for Action Anticipation via Label Smoothing
Guglielmo Camporese, Pasquale Coscia, Antonino Furnari +2
Human capability to anticipate near future from visual observations and non-verbal cues is essential for developing intelligent systems that need to interact with people. Several r…
A CNN-RNN Framework for Image Annotation from Visual Cues and Social Network Metadata
Tobia Tesan, Pasquale Coscia, Lamberto Ballan
Images represent a commonly used form of visual communication among people. Nevertheless, image classification may be a challenging task when dealing with unclear or non-common ima…
Social and Scene-Aware Trajectory Prediction in Crowded Spaces
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 socia…
Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition
Christian Rupprecht, Ansh Kapil, Nan Liu +2
Webly-supervised learning has recently emerged as an alternative paradigm to traditional supervised learning based on large-scale datasets with manual annotations. The key idea is…
Localization of JPEG double compression through multi-domain convolutional neural networks
Irene Amerini, Tiberio Uricchio, Lamberto Ballan +1
When an attacker wants to falsify an image, in most of cases she/he will perform a JPEG recompression. Different techniques have been developed based on diverse theoretical assumpt…
Context-Aware Trajectory Prediction
Federico Bartoli, Giuseppe Lisanti, Lamberto Ballan +1
Human motion and behaviour in crowded spaces is influenced by several factors, such as the dynamics of other moving agents in the scene, as well as the static elements that might b…
Am I Done? Predicting Action Progress in Videos
Federico Becattini, Tiberio Uricchio, Lorenzo Seidenari +2
In this paper we deal with the problem of predicting action progress in videos. We argue that this is an extremely important task since it can be valuable for a wide range of inter…
Automatic Image Annotation via Label Transfer in the Semantic Space
Tiberio Uricchio, Lamberto Ballan, Lorenzo Seidenari +1
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 th…