8 papers
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…
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…
Weight Space Representation Learning on Diverse NeRF Architectures
Francesco Ballerini, Pierluigi Zama Ramirez, Luigi Di Stefano +1
Neural Radiance Fields (NeRFs) have emerged as a groundbreaking paradigm for representing 3D objects and scenes by encoding shape and appearance information into the weights of a n…
NVS-HO: A Benchmark for Novel View Synthesis of Handheld Objects
Musawar Ali, Manuel Carranza-GarcÃa, Nicola Fioraio +2
We propose NVS-HO, the first benchmark designed for novel view synthesis of handheld objects in real-world environments using only RGB inputs. Each object is recorded in two comple…
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…
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…