3 papers
cs.CV2025
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…
cs.CV2025
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…
cs.CV2025
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…