Pietro Zanuttigh | DeepAI

DeepAI AI Chat

Featured Co-authors

Chang Liu
231 publications
Michele Zorzi
118 publications
Marco Giordani
51 publications
Yi Niu
26 publications
Umberto Michieli
23 publications
Fabien Cardinaux
13 publications
Paolo Testolina
12 publications
Mattia Rossi
9 publications
Marco Toldo
9 publications
Simone Milani
9 publications
Francesco Barbato
8 publications

∙ 09/19/2023

RECALL+: Adversarial Web-based Replay for Continual Learning in Semantic Segmentation

Catastrophic forgetting of previous knowledge is a critical issue in con...

0 Chang Liu, et al. ∙

∙ 09/13/2023

Exploiting Multiple Priors for Neural 3D Indoor Reconstruction

Neural implicit modeling permits to achieve impressive 3D reconstruction...

0 Federico Lincetto, et al. ∙

∙ 08/21/2023

SynDrone – Multi-modal UAV Dataset for Urban Scenarios

The development of computer vision algorithms for Unmanned Aerial Vehicl...

0 Giulia Rizzoli, et al. ∙

∙ 08/09/2023

Continual Road-Scene Semantic Segmentation via Feature-Aligned Symmetric Multi-Modal Network

State-of-the-art multimodal semantic segmentation approaches combining L...

0 Francesco Barbato, et al. ∙

∙ 05/23/2023

Source-Free Domain Adaptation for RGB-D Semantic Segmentation with Vision Transformers

With the increasing availability of depth sensors, multimodal frameworks...

0 Giulia Rizzoli, et al. ∙

∙ 04/07/2023

Asynchronous Federated Continual Learning

The standard class-incremental continual learning setting assumes a set ...

0 Donald Shenaj, et al. ∙

∙ 11/08/2022

DepthFormer: Multimodal Positional Encodings and Cross-Input Attention for Transformer-Based Segmentation Networks

Most approaches for semantic segmentation use only information from colo...

0 Francesco Barbato, et al. ∙

∙ 10/13/2022

Learning with Style: Continual Semantic Segmentation Across Tasks and Domains

Deep learning models dealing with image understanding in real-world sett...

0 Marco Toldo, et al. ∙

∙ 05/25/2022

A Low Memory Footprint Quantized Neural Network for Depth Completion of Very Sparse Time-of-Flight Depth Maps

Sparse active illumination enables precise time-of-flight depth sensing ...

0 Xiaowen Jiang, et al. ∙

∙ 04/20/2022

SELMA: SEmantic Large-scale Multimodal Acquisitions in Variable Weather, Daytime and Viewpoints

Accurate scene understanding from multiple sensors mounted on cars is a ...

8 Paolo Testolina, et al. ∙

∙ 04/14/2022

End-to-end Learning for Joint Depth and Image Reconstruction from Diffracted Rotation

Monocular depth estimation is still an open challenge due to the ill-pos...

11 Mazen Mel, et al. ∙

∙ 01/18/2022

Continual Coarse-to-Fine Domain Adaptation in Semantic Segmentation

Deep neural networks are typically trained in a single shot for a specif...

12 Donald Shenaj, et al. ∙

∙ 11/29/2021

Lightweight Deep Learning Architecture for MPI Correction and Transient Reconstruction

Indirect Time-of-Flight cameras (iToF) are low-cost devices that provide...

0 Adriano Simonetto, et al. ∙

∙ 08/08/2021

RECALL: Replay-based Continual Learning in Semantic Segmentation

Deep networks allow to obtain outstanding results in semantic segmentati...

8 Andrea Maracani, et al. ∙

∙ 08/06/2021

Adapting Segmentation Networks to New Domains by Disentangling Latent Representations

Deep learning models achieve outstanding accuracy in semantic segmentati...

32 Francesco Barbato, et al. ∙

∙ 04/06/2021

Latent Space Regularization for Unsupervised Domain Adaptation in Semantic Segmentation

Deep convolutional neural networks for semantic segmentation allow to ac...

0 Francesco Barbato, et al. ∙

∙ 03/10/2021

Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations

Deep neural networks suffer from the major limitation of catastrophic fo...

10 Umberto Michieli, et al. ∙

∙ 11/25/2020

Unsupervised Domain Adaptation in Semantic Segmentation via Orthogonal and Clustered Embeddings

Deep learning frameworks allowed for a remarkable advancement in semanti...

7 Marco Toldo, et al. ∙

∙ 07/17/2020

GMNet: Graph Matching Network for Large Scale Part Semantic Segmentation in the Wild

The semantic segmentation of parts of objects in the wild is a challengi...

0 Umberto Michieli, et al. ∙

∙ 05/21/2020

Unsupervised Domain Adaptation in Semantic Segmentation: a Review

The aim of this paper is to give an overview of the recent advancements ...

0 Marco Toldo, et al. ∙

∙ 04/27/2020

Unsupervised Domain Adaptation with Multiple Domain Discriminators and Adaptive Self-Training

Unsupervised Domain Adaptation (UDA) aims at improving the generalizatio...

0 Teo Spadotto, et al. ∙

∙ 01/14/2020

Unsupervised Domain Adaptation for Mobile Semantic Segmentation based on Cycle Consistency and Feature Alignment

The supervised training of deep networks for semantic segmentation requi...

5 Marco Toldo, et al. ∙

∙ 11/08/2019

Knowledge Distillation for Incremental Learning in Semantic Segmentation

Although deep learning architectures have shown remarkable results in sc...

31 Umberto Michieli, et al. ∙

∙ 09/02/2019

Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation

Deep learning techniques have been widely used in autonomous driving sys...

21 Umberto Michieli, et al. ∙

∙ 07/31/2019

Incremental Learning Techniques for Semantic Segmentation

Deep learning architectures exhibit a critical drop of performance due t...

0 Umberto Michieli, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world