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08/22/2023
TrackFlow: Multi-Object Tracking with Normalizing Flows
The field of multi-object tracking has recently seen a renewed interest ...
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05/05/2023
On the Effectiveness of Equivariant Regularization for Robust Online Continual Learning
Humans can learn incrementally, whereas neural networks forget previousl...
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02/02/2023
Neuro Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal
We introduce Neuro-Symbolic Continual Learning, where a model has to sol...
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01/27/2023
Input Perturbation Reduces Exposure Bias in Diffusion Models
Denoising Diffusion Probabilistic Models have shown an impressive genera...
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01/09/2023
CaSpeR: Latent Spectral Regularization for Continual Learning
While biological intelligence grows organically as new knowledge is gath...
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10/12/2022
On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning
Rehearsal approaches enjoy immense popularity with Continual Learning (C...
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09/07/2022
Spotting Virus from Satellites: Modeling the Circulation of West Nile Virus Through Graph Neural Networks
The occurrence of West Nile Virus (WNV) represents one of the most commo...
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08/10/2022
Consistency-based Self-supervised Learning for Temporal Anomaly Localization
This work tackles Weakly Supervised Anomaly detection, in which a predic...
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07/07/2022
Learning the Quality of Machine Permutations in Job Shop Scheduling
In recent years, the power demonstrated by Machine Learning (ML) has inc...
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06/03/2022
Effects of Auxiliary Knowledge on Continual Learning
In Continual Learning (CL), a neural network is trained on a stream of d...
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06/01/2022
Transfer without Forgetting
This work investigates the entanglement between Continual Learning (CL) ...
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04/25/2022
Goal-driven Self-Attentive Recurrent Networks for Trajectory Prediction
Human trajectory forecasting is a key component of autonomous vehicles, ...
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03/09/2022
How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting
Accurate prediction of future human positions is an essential task for m...
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01/03/2022
Class-Incremental Continual Learning into the eXtended DER-verse
The staple of human intelligence is the capability of acquiring knowledg...
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08/21/2021
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?
Deep learning-based methods for video pedestrian detection and tracking ...
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08/14/2021
Weakly Supervised Continual Learning
Continual Learning (CL) investigates how to train Deep Networks on a str...
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02/15/2021
RMS-Net: Regression and Masking for Soccer Event Spotting
The recently proposed action spotting task consists in finding the exact...
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01/28/2021
Generalising via Meta-Examples for Continual Learning in the Wild
Learning quickly and continually is still an ambitious task for neural n...
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10/12/2020
Rethinking Experience Replay: a Bag of Tricks for Continual Learning
In Continual Learning, a Neural Network is trained on a stream of data w...
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09/17/2020
Few-Shot Unsupervised Continual Learning through Meta-Examples
In real-world applications, data do not reflect the ones commonly used f...
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07/20/2020
Inter-Homines: Distance-Based Risk Estimation for Human Safety
In this document, we report our proposal for modeling the risk of possib...
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07/08/2020
Robust Re-Identification by Multiple Views Knowledge Distillation
To achieve robustness in Re-Identification, standard methods leverage tr...
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07/01/2020
Future Urban Scenes Generation Through Vehicles Synthesis
In this work we propose a deep learning pipeline to predict the visual f...
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06/22/2020
The color out of space: learning self-supervised representations for Earth Observation imagery
The recent growth in the number of satellite images fosters the developm...
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05/26/2020
DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting
Understanding human motion behaviour is a critical task for several poss...
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05/17/2020
AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction
Anticipating human motion in crowded scenarios is essential for developi...
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04/15/2020
Dark Experience for General Continual Learning: a Strong, Simple Baseline
Neural networks struggle to learn continuously, as they forget the old k...
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04/01/2020
Compressed Volumetric Heatmaps for Multi-Person 3D Pose Estimation
In this paper we present a novel approach for bottom-up multi-person 3D ...
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03/31/2020
Conditional Channel Gated Networks for Task-Aware Continual Learning
Convolutional Neural Networks experience catastrophic forgetting when op...
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12/09/2019
STAGE: Spatio-Temporal Attention on Graph Entities for Video Action Detection
Spatio-temporal action localization is a challenging yet fascinating tas...
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11/22/2019
Spotting insects from satellites: modeling the presence of Culicoides imicola through Deep CNNs
Nowadays, Vector-Borne Diseases (VBDs) raise a severe threat for public ...
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07/24/2019
Semi-parametric Object Synthesis
We present a new semi-parametric approach to synthesize novel views of a...
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03/05/2019
A Deep Learning based approach to VM behavior identification in cloud systems
Cloud computing data centers are growing in size and complexity to the p...
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02/13/2019
Multi-views Embedding for Cattle Re-identification
People re-identification task has seen enormous improvements in the late...
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02/13/2019
Classifying Signals on Irregular Domains via Convolutional Cluster Pooling
We present a novel and hierarchical approach for supervised classificati...
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01/23/2019
Domain Translation with Conditional GANs: from Depth to RGB Face-to-Face
Can faces acquired by low-cost depth sensors be useful to catch some cha...
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01/23/2019
Can Adversarial Networks Hallucinate Occluded People With a Plausible Aspect?
When you see a person in a crowd, occluded by other persons, you miss vi...
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07/04/2018
AND: Autoregressive Novelty Detectors
We propose an unsupervised model for novelty detection. The subject is t...
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03/22/2018
Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World
Multi-People Tracking in an open-world setting requires a special effort...
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12/12/2017
Face-from-Depth for Head Pose Estimation on Depth Images
Depth cameras allow to setup reliable solutions for people monitoring an...
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07/07/2017
Generative Adversarial Models for People Attribute Recognition in Surveillance
In this paper we propose a deep architecture for detecting people attrib...
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06/26/2017
Learning to Map Vehicles into Bird's Eye View
Awareness of the road scene is an essential component for both autonomou...
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06/01/2017
TransFlow: Unsupervised Motion Flow by Joint Geometric and Pixel-level Estimation
We address unsupervised optical flow estimation for ego-centric motion. ...
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05/10/2017
Predicting the Driver's Focus of Attention: the DR(eye)VE Project
In this work we aim to predict the driver's focus of attention. The goal...
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11/24/2016
Learning Where to Attend Like a Human Driver
Despite the advent of autonomous cars, it's likely - at least in the nea...
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09/14/2015