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cs.CV2026
RADIOlogy: A Single-Pass Approach to Training-Free Zero-Shot Anomaly Detection
Joaquín Figueira, Giacomo D'Amicantonio, Egor Bondarau
Current zero-shot anomaly detection methods often rely on complex prompt-learning techniques or computationally expensive sliding-window strategies to achieve fine-grained visual a…
cs.CV2026
BenthicFlow: Generating Extensible Underwater Environments via Flow Matching
Joaquín Figueira, Camile Lendering, Manfred Gonzalez-Hernandez +3
Computer vision applications for 3D scene understanding in underwater environments remain challenging due to the lack of high-quality 3D data and the inability of surface-trained m…
cs.CV2026
AOI-SSL: Self-Supervised Framework for Efficient Segmentation of Wire-bonded Semiconductors In Optical Inspection
Joaquín Figueira, Rob Van Gastel, Giacomo D'Amicantonio +4
Segmentation models in automated optical inspection of wire-bonded semiconductors are typically device-specific and must be re-trained when new devices or distribution shifts appea…