12 citations · 12 across the 3 of their papers we have counts for
4 papers
A Structured Benchmark for Text-Guided Anomaly Detection: When Language Stops Conditioning the Decision
Stefano Samele, Eugenio Lomurno, Teodora Jovanovic +3
Industrial anomaly detection has historically been a unimodal task. Recent multimodal vision-language models have produced systems that admit textual input alongside the image and…
MARS: a Multimodal Alignment and Ranking System for Few-Shot Segmentation
Nico Catalano, Stefano Samele, Paolo Pertino +1
Few Shot Segmentation aims to segment novel object classes given only a handful of labeled examples, enabling rapid adaptation with minimal supervision. Current literature cruciall…
More than the Sum of Its Parts: Ensembling Backbone Networks for Few-Shot Segmentation
Nico Catalano, Alessandro Maranelli, Agnese Chiatti +1
Semantic segmentation is a key prerequisite to robust image understanding for applications in \acrlong{ai} and Robotics. \acrlong{fss}, in particular, concerns the extension and op…
Few Shot Semantic Segmentation: a review of methodologies, benchmarks, and open challenges
Nico Catalano, Matteo Matteucci
Semantic segmentation, vital for applications ranging from autonomous driving to robotics, faces significant challenges in domains where collecting large annotated datasets is diff…