Zero-OVCD generates change pseudo-labels from SAM3, DINOv3, and SegEarth-OV3, then trains a change detector on them, lifting F1 to 88.65%, 88.85%, and 57.96% on LEVIR-CD, WHU-CD, and S2Looking without target-domain pixel labels.
Fully convolutional siamese networks for change detection,
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Zero-OVCD: Bridging Training-Free Foundation Models and Pseudo-Label Learning for Open-Vocabulary Change Detection
Zero-OVCD generates change pseudo-labels from SAM3, DINOv3, and SegEarth-OV3, then trains a change detector on them, lifting F1 to 88.65%, 88.85%, and 57.96% on LEVIR-CD, WHU-CD, and S2Looking without target-domain pixel labels.