1 citations · 1 across the 6 of their papers we have counts for
6 papers
Cracks in the Foundation: A Civil Infrastructure Dataset to Challenge Vision Foundation Models
Nicola Farronato, Niccolo Avogaro, Thomas Frick +6
Automated structural health monitoring is essential to prevent catastrophic infrastructure failures. Precise, pixel-level defect segmentation is needed to accurately assess structu…
PicoSAM3: Real-Time In-Sensor Region-of-Interest Segmentation
Pietro Bonazzi, Nicola Farronato, Stefan Zihlmann +2
Real-time, on-device segmentation is critical for latency-sensitive and privacy-aware applications such as smart glasses and Internet-of-Things devices. We introduce PicoSAM3, a li…
PicoSAM2: Low-Latency Segmentation In-Sensor for Edge Vision Applications
Pietro Bonazzi, Nicola Farronato, Stefan Zihlmann +2
Real-time, on-device segmentation is critical for latency-sensitive and privacy-aware applications like smart glasses and IoT devices. We introduce PicoSAM2, a lightweight (1.3M pa…
Q-SAM2: Accurate Quantization for Segment Anything Model 2
Nicola Farronato, Florian Scheidegger, Mattia Rigotti +3
The Segment Anything Model 2 (SAM2) is a powerful foundation model for promptable segmentation. However, its high computational and memory costs are a major barrier to deployment o…
VP Lab: a PEFT-Enabled Visual Prompting Laboratory for Semantic Segmentation
Niccolo Avogaro, Thomas Frick, Yagmur G. Cinar +12
Large-scale pretrained vision backbones have transformed computer vision by providing powerful feature extractors that enable various downstream tasks, including training-free appr…
Invisible Threats: Backdoor Attack in OCR Systems
Mauro Conti, Nicola Farronato, Stefanos Koffas +2
Optical Character Recognition (OCR) is a widely used tool to extract text from scanned documents. Today, the state-of-the-art is achieved by exploiting deep neural networks. Howeve…