activity
20232026
most citedClaycode: Stylable and Deformable 2D Scannable Codes

1 citations · 2 across the 8 of their papers we have counts for

collaborators

9 papers

cs.GR2026

Split&Splat: Zero-Shot Panoptic Segmentation via Explicit Instance Modeling and 3D Gaussian Splatting

Leonardo Monchieri, Elena Camuffo, Francesco Barbato +2

3D Gaussian Splatting (GS) enables fast and high-quality scene reconstruction, but it lacks an object-consistent and semantically aware structure. We propose Split&Splat, a framewo…

cs.CV2025

MOCHA: Multi-modal Objects-aware Cross-arcHitecture Alignment

Elena Camuffo, Francesco Barbato, Mete Ozay +2

Personalized object detection aims to adapt a general-purpose detector to recognize user-specific instances from only a few examples. Lightweight models often struggle in this sett…

cs.GR2025★ 1 cited

Claycode: Stylable and Deformable 2D Scannable Codes

Marco Maida, Alberto Crescini, Marco Perronet +1

This paper introduces Claycode, a novel 2D scannable code designed for extensive stylization and deformation. Unlike traditional matrix-based codes (e.g., QR codes), Claycodes enco…

cs.GR2025

SAGE: Semantic-Driven Adaptive Gaussian Splatting in Extended Reality

Chiara Schiavo, Elena Camuffo, Leonardo Badia +1

3D Gaussian Splatting (3DGS) has significantly improved the efficiency and realism of three-dimensional scene visualization in several applications, ranging from robotics to eXtend…

cs.CV2024

Enhanced Model Robustness to Input Corruptions by Per-corruption Adaptation of Normalization Statistics

Elena Camuffo, Umberto Michieli, Simone Milani +2

Developing a reliable vision system is a fundamental challenge for robotic technologies (e.g., indoor service robots and outdoor autonomous robots) which can ensure reliable naviga…

cs.CV2024

FFT-based Selection and Optimization of Statistics for Robust Recognition of Severely Corrupted Images

Elena Camuffo, Umberto Michieli, Jijoong Moon +2

Improving model robustness in case of corrupted images is among the key challenges to enable robust vision systems on smart devices, such as robotic agents. Particularly, robust te…

cs.CV2023★ 1 cited

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

Francesco Barbato, Elena Camuffo, Simone Milani +1

State-of-the-art multimodal semantic segmentation strategies combining LiDAR and color data are usually designed on top of asymmetric information-sharing schemes and assume that bo…

cs.CV2023

Continual Learning for LiDAR Semantic Segmentation: Class-Incremental and Coarse-to-Fine strategies on Sparse Data

Elena Camuffo, Simone Milani

During the last few years, continual learning (CL) strategies for image classification and segmentation have been widely investigated designing innovative solutions to tackle catas…

cs.CV2023

Learning from Mistakes: Self-Regularizing Hierarchical Representations in Point Cloud Semantic Segmentation

Elena Camuffo, Umberto Michieli, Simone Milani

Recent advances in autonomous robotic technologies have highlighted the growing need for precise environmental analysis. LiDAR semantic segmentation has gained attention to accompl…