activity
20232026
most citedMultimodal Industrial Anomaly Detection by Crossmodal Feature Mapping

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

collaborators

9 papers

cs.CV2026

Spectral Gating via Damped Oscillations for Adaptive Implicit Neural Representations

Alex Costanzino, Pierluigi Zama Ramirez, Giuseppe Lisanti +1

Implicit Neural Representations (INRs) have been proven successful in encoding continuous signals through coordinate-based networks, yet facing a spectral dilemma: periodic activat…

cs.CV2026

Modulate-and-Map: Crossmodal Feature Mapping with Cross-View Modulation for 3D Anomaly Detection

Alex Costanzino, Pierluigi Zama Ramirez, Giuseppe Lisanti +1

We present ModMap, a natively multiview and multimodal framework for 3D anomaly detection and segmentation. Unlike existing methods that process views independently, our method dra…

cs.CV2025

SiM3D: Single-instance Multiview Multimodal and Multisetup 3D Anomaly Detection Benchmark

Alex Costanzino, Pierluigi Zama Ramirez, Luigi Lella +4

We propose SiM3D, the first benchmark considering the integration of multiview and multimodal information for comprehensive 3D anomaly detection and segmentation (ADS), where the t…

cs.CV2025

Scaling LLaNA: Advancing NeRF-Language Understanding Through Large-Scale Training

Andrea Amaduzzi, Pierluigi Zama Ramirez, Giuseppe Lisanti +2

Recent advances in Multimodal Large Language Models (MLLMs) have shown remarkable capabilities in understanding both images and 3D data, yet these modalities face inherent limitati…

cs.CV2024★ 1 cited

Learning to Be a Transformer to Pinpoint Anomalies

Alex Costanzino, Pierluigi Zama Ramirez, Giuseppe Lisanti +1

To efficiently deploy strong, often pre-trained feature extractors, recent Industrial Anomaly Detection and Segmentation (IADS) methods process low-resolution images, e.g., 224x224…

cs.CV2024

LLaNA: Large Language and NeRF Assistant

Andrea Amaduzzi, Pierluigi Zama Ramirez, Giuseppe Lisanti +2

Multimodal Large Language Models (MLLMs) have demonstrated an excellent understanding of images and 3D data. However, both modalities have shortcomings in holistically capturing th…

cs.CV2024

Test Time Training for Industrial Anomaly Segmentation

Alex Costanzino, Pierluigi Zama Ramirez, Mirko Del Moro +4

Anomaly Detection and Segmentation (AD&S) is crucial for industrial quality control. While existing methods excel in generating anomaly scores for each pixel, practical application…

cs.CV2023★ 2 cited

Multimodal Industrial Anomaly Detection by Crossmodal Feature Mapping

Alex Costanzino, Pierluigi Zama Ramirez, Giuseppe Lisanti +1

The paper explores the industrial multimodal Anomaly Detection (AD) task, which exploits point clouds and RGB images to localize anomalies. We introduce a novel light and fast fram…

cs.CV2023

Looking at words and points with attention: a benchmark for text-to-shape coherence

Andrea Amaduzzi, Giuseppe Lisanti, Samuele Salti +1

While text-conditional 3D object generation and manipulation have seen rapid progress, the evaluation of coherence between generated 3D shapes and input textual descriptions lacks…