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cs.CV2024
Self-Supervised Anomaly Detection in the Wild: Favor Joint Embeddings Methods
Daniel Otero, Rafael Mateus, Randall Balestriero
Accurate anomaly detection is critical in vision-based infrastructure inspection, where it helps prevent costly failures and enhances safety. Self-Supervised Learning (SSL) offers…
cs.CV2024
Self-Supervised Learning for Identifying Defects in Sewer Footage
Daniel Otero, Rafael Mateus
Sewerage infrastructure is among the most expensive modern investments requiring time-intensive manual inspections by qualified personnel. Our study addresses the need for automate…