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Image -> AnomalyMap
Segment anomalies in an image by computing the spatial similarity between dense visual embeddings and contrasting textual prompts representing normal vs anomalous states.
Problem it solves
Training specific anomaly detection models from scratch requires large, domain-specific normal datasets.
Consumes
Emits
The real projects this mechanism was found in. Attribution is the point — this is how the best teams actually do it.