activity
20242026
most citedCross-Domain Transfer Learning with CoRTe: Consistent and Reliable Transfer from Black-Box to Lightweight Segmentation Model

3 citations · 4 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CV2026

FoundYou: A Unified Model for Personalized Segmentation and Retrieval

Gabriele Trivigno, Marcos Alfaro, Claudia Cuttano +3

Personalized segmentation and personalized retrieval both aim to identify the same physical object across different images. While the former localizes the object within a target im…

cs.CV2026

MARCO: Navigating the Unseen Space of Semantic Correspondence

Claudia Cuttano, Gabriele Trivigno, Carlo Masone +1

Recent advances in semantic correspondence rely on dual-encoder architectures, combining DINOv2 with diffusion backbones. While accurate, these billion-parameter models generalize…

cs.CV2026

INSID3: Training-Free In-Context Segmentation with DINOv3

Claudia Cuttano, Gabriele Trivigno, Christoph Reich +3

In-context segmentation (ICS) aims to segment arbitrary concepts, e.g., objects, parts, or personalized instances, given one annotated visual examples. Existing work relies on (i)…

cs.CV2025★ 1 cited

Φeat: Physically Grounded Material Feature Representation

Giuseppe Vecchio, Adrien Kaiser, Claudia Cuttano +4

While foundation models have emerged as general-purpose visual backbones, their representations are primarily optimized for semantics and lack explicit modeling of physical factors…

cs.CV2025

SANSA: Unleashing the Hidden Semantics in SAM2 for Few-Shot Segmentation

Claudia Cuttano, Gabriele Trivigno, Giuseppe Averta +1

Few-shot segmentation aims to segment unseen object categories from just a handful of annotated examples. This requires mechanisms that can both identify semantically related objec…

cs.CV2024

SAMWISE: Infusing Wisdom in SAM2 for Text-Driven Video Segmentation

Claudia Cuttano, Gabriele Trivigno, Gabriele Rosi +2

Referring Video Object Segmentation (RVOS) relies on natural language expressions to segment an object in a video clip. Existing methods restrict reasoning either to independent sh…

cs.CV2024

What does CLIP know about peeling a banana?

Claudia Cuttano, Gabriele Rosi, Gabriele Trivigno +1

Humans show an innate capability to identify tools to support specific actions. The association between objects parts and the actions they facilitate is usually named affordance. B…

cs.CV2024

The revenge of BiSeNet: Efficient Multi-Task Image Segmentation

Gabriele Rosi, Claudia Cuttano, Niccolò Cavagnero +2

Recent advancements in image segmentation have focused on enhancing the efficiency of the models to meet the demands of real-time applications, especially on edge devices. However,…

cs.CV2024★ 3 cited

Cross-Domain Transfer Learning with CoRTe: Consistent and Reliable Transfer from Black-Box to Lightweight Segmentation Model

Claudia Cuttano, Antonio Tavera, Fabio Cermelli +2

Many practical applications require training of semantic segmentation models on unlabelled datasets and their execution on low-resource hardware. Distillation from a trained source…

cs.CV2024

PEM: Prototype-based Efficient MaskFormer for Image Segmentation

Niccolò Cavagnero, Gabriele Rosi, Claudia Cuttano +4

Recent transformer-based architectures have shown impressive results in the field of image segmentation. Thanks to their flexibility, they obtain outstanding performance in multipl…