b'Elisa Ricci'

research

∙ 08/28/2023

Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation

Deep-learning models for 3D point cloud semantic segmentation exhibit li...

0 Cristiano Saltori, et al. ∙

research

∙ 08/18/2023

On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers

State-of-the-art rehearsal-free continual learning methods exploit the p...

0 Thomas De Min, et al. ∙

research

∙ 08/17/2023

The Unreasonable Effectiveness of Large Language-Vision Models for Source-free Video Domain Adaptation

Source-Free Video Unsupervised Domain Adaptation (SFVUDA) methods consis...

0 Giacomo Zara, et al. ∙

research

∙ 07/31/2023

Interactive Neural Painting

In the last few years, Neural Painting (NP) techniques became capable of...

0 Elia Peruzzo, et al. ∙

research

∙ 07/18/2023

Object-aware Gaze Target Detection

Gaze target detection aims to predict the image location where the perso...

0 Francesco Tonini, et al. ∙

research

∙ 07/04/2023

Unsupervised Video Anomaly Detection with Diffusion Models Conditioned on Compact Motion Representations

This paper aims to address the unsupervised video anomaly detection (VAD...

0 Anil Osman Tur, et al. ∙

research

∙ 06/13/2023

Semi-supervised learning made simple with self-supervised clustering

Self-supervised learning models have been shown to learn rich visual rep...

0 Enrico Fini, et al. ∙

research

∙ 05/09/2023

Rotation Synchronization via Deep Matrix Factorization

In this paper we address the rotation synchronization problem, where the...

0 Gk Tejus, et al. ∙

research

∙ 04/23/2023

Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation

The ability to deploy robots that can operate safely in diverse environm...

2 Cristiano Saltori, et al. ∙

research

∙ 04/12/2023

Exploring Diffusion Models for Unsupervised Video Anomaly Detection

This paper investigates the performance of diffusion models for video an...

0 Anil Osman Tur, et al. ∙

research

∙ 04/03/2023

AutoLabel: CLIP-based framework for Open-set Video Domain Adaptation

Open-set Unsupervised Video Domain Adaptation (OUVDA) deals with the tas...

0 Giacomo Zara, et al. ∙

research

∙ 03/28/2023

Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery

Discovering novel concepts from unlabelled data and in a continuous mann...

0 Mingxuan Liu, et al. ∙

research

∙ 03/27/2023

Quantum Multi-Model Fitting

Geometric model fitting is a challenging but fundamental computer vision...

0 Matteo Farina, et al. ∙

research

∙ 03/23/2023

Plotting Behind the Scenes: Towards Learnable Game Engines

Game engines are powerful tools in computer graphics. Their power comes ...

0 Willi Menapace, et al. ∙

research

∙ 03/21/2023

Novel Class Discovery for 3D Point Cloud Semantic Segmentation

Novel class discovery (NCD) for semantic segmentation is the task of lea...

0 Luigi Riz, et al. ∙

research

∙ 02/18/2023

StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalization

Large-scale foundation models (e.g., CLIP) have shown promising zero-sho...

0 Shirsha Bose, et al. ∙

research

∙ 01/09/2023

Simplifying Open-Set Video Domain Adaptation with Contrastive Learning

In an effort to reduce annotation costs in action recognition, unsupervi...

0 Giacomo Zara, et al. ∙

research

∙ 12/09/2022

A soft nearest-neighbor framework for continual semi-supervised learning

Despite significant advances, the performance of state-of-the-art contin...

0 Zhiqi Kang, et al. ∙

research

∙ 10/17/2022

Overlap-guided Gaussian Mixture Models for Point Cloud Registration

Probabilistic 3D point cloud registration methods have shown competitive...

5 Guofeng Mei, et al. ∙

research

∙ 10/06/2022

Data Augmentation-free Unsupervised Learning for 3D Point Cloud Understanding

Unsupervised learning on 3D point clouds has undergone a rapid evolution...

14 Guofeng Mei, et al. ∙

research

∙ 10/04/2022

Cooperative Self-Training for Multi-Target Adaptive Semantic Segmentation

In this work we address multi-target domain adaptation (MTDA) in semanti...

11 Yangsong Zhang, et al. ∙

research

∙ 08/23/2022

Multimodal Across Domains Gaze Target Detection

This paper addresses the gaze target detection problem in single images ...

7 Francesco Tonini, et al. ∙

research

∙ 08/16/2022

Uncertainty-guided Source-free Domain Adaptation

Source-free domain adaptation (SFDA) aims to adapt a classifier to an un...

14 Subhankar Roy, et al. ∙

research

∙ 07/23/2022

Multimodal Emotion Recognition with Modality-Pairwise Unsupervised Contrastive Loss

Emotion recognition is involved in several real-world applications. With...

22 Riccardo Franceschini, et al. ∙

research

∙ 07/20/2022

CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation

3D LiDAR semantic segmentation is fundamental for autonomous driving. Se...

0 Cristiano Saltori, et al. ∙

research

∙ 07/20/2022

GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation

3D point cloud semantic segmentation is fundamental for autonomous drivi...

0 Cristiano Saltori, et al. ∙

research

∙ 07/18/2022

Class-incremental Novel Class Discovery

We study the new task of class-incremental Novel Class Discovery (class-...

14 Subhankar Roy, et al. ∙

research

∙ 03/26/2022

Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation

A fundamental and challenging problem in deep learning is catastrophic f...

17 Guanglei Yang, et al. ∙

research

∙ 03/24/2022

Quantum Motion Segmentation

Motion segmentation is a challenging problem that seeks to identify inde...

4 Federica Arrigoni, et al. ∙

research

∙ 03/03/2022

Playable Environments: Video Manipulation in Space and Time

We present Playable Environments - a new representation for interactive ...

2 Willi Menapace, et al. ∙

research

∙ 02/07/2022

3D Object Detection from Images for Autonomous Driving: A Survey

3D object detection from images, one of the fundamental and challenging ...

18 Xinzhu Ma, et al. ∙

research

∙ 02/01/2022

Continual Attentive Fusion for Incremental Learning in Semantic Segmentation

Over the past years, semantic segmentation, as many other tasks in compu...

26 Guanglei Yang, et al. ∙

research

∙ 01/31/2022

Modeling the Background for Incremental and Weakly-Supervised Semantic Segmentation

Deep neural networks have enabled major progresses in semantic segmentat...

14 Fabio Cermelli, et al. ∙

research

∙ 12/08/2021

Self-Supervised Models are Continual Learners

Self-supervised models have been shown to produce comparable or better v...

0 Enrico Fini, et al. ∙

research

∙ 11/19/2021

Global and Local Alignment Networks for Unpaired Image-to-Image Translation

The goal of unpaired image-to-image translation is to produce an output ...

6 Guanglei Yang, et al. ∙

research

∙ 11/19/2021

Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation

In autonomous driving, learning a segmentation model that can adapt to v...

0 Guanglei Yang, et al. ∙

research

∙ 08/19/2021

Click to Move: Controlling Video Generation with Sparse Motion

This paper introduces Click to Move (C2M), a novel framework for video g...

3 Pierfrancesco Ardino, et al. ∙

research

∙ 08/19/2021

A Unified Objective for Novel Class Discovery

In this paper, we study the problem of Novel Class Discovery (NCD). NCD ...

0 Enrico Fini, et al. ∙

research

∙ 08/03/2021

Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning

This paper presents solo-learn, a library of self-supervised methods for...

0 Victor G. Turrisi da Costa, et al. ∙

research

∙ 06/20/2021

Neighborhood Contrastive Learning for Novel Class Discovery

In this paper, we address Novel Class Discovery (NCD), the task of unvei...

0 Zhun Zhong, et al. ∙

research

∙ 05/28/2021

Transformer-Based Source-Free Domain Adaptation

In this paper, we study the task of source-free domain adaptation (SFDA)...

0 Guanglei Yang, et al. ∙

research

∙ 04/01/2021

Curriculum Graph Co-Teaching for Multi-Target Domain Adaptation

In this paper we address multi-target domain adaptation (MTDA), where gi...

0 Subhankar Roy, et al. ∙

research

∙ 03/25/2021

Boosting Binary Masks for Multi-Domain Learning through Affine Transformations

In this work, we present a new, algorithm for multi-domain learning. Giv...

0 Massimiliano Mancini, et al. ∙

research

∙ 03/25/2021

Inferring Latent Domains for Unsupervised Deep Domain Adaptation

Unsupervised Domain Adaptation (UDA) refers to the problem of learning a...

0 Massimiliano Mancini, et al. ∙

research

∙ 03/22/2021

Transformers Solve the Limited Receptive Field for Monocular Depth Prediction

While convolutional neural networks have shown a tremendous impact on va...

13 Guanglei Yang, et al. ∙

research

∙ 03/05/2021

Variational Structured Attention Networks for Deep Visual Representation Learning

Convolutional neural networks have enabled major progress in addressing ...

9 Guanglei Yang, et al. ∙

research

∙ 01/28/2021

Playable Video Generation

This paper introduces the unsupervised learning problem of playable vide...

1 Willi Menapace, et al. ∙

research

∙ 01/11/2021

Multi-Domain Image-to-Image Translation with Adaptive Inference Graph

In this work, we address the problem of multi-domain image-to-image tran...

8 The-Phuc Nguyen, et al. ∙

research

∙ 01/08/2021

Probabilistic Graph Attention Network with Conditional Kernels for Pixel-Wise Prediction

Multi-scale representations deeply learned via convolutional neural netw...

17 Dan Xu, et al. ∙

research

∙ 12/10/2020

Demystifying Pseudo-LiDAR for Monocular 3D Object Detection

Pseudo-LiDAR-based methods for monocular 3D object detection have genera...

0 Andrea Simonelli, et al. ∙

Elisa Ricci

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