PASTA: Vision Transformer Patch Aggregation for Weakly Supervised Target and Anomaly Segmentation

ArXi:2604.09701v1 Announce Type: cross Detecting unseen anomalies in unstructured environments presents a critical challenge for industrial and agricultural applications such as material recycling and weeding. Existing perception systems frequently fail to satisfy the strict operational requirements of these domains, specifically real-time processing, pixel-level segmentation precision, and robust accuracy, due to their reliance on exhaustively annotated datasets.