TopoTTA integrates persistent homology into test-time adaptation to derive topological pseudo-labels from anomaly maps, improving segmentation by an average 15% F1 on six benchmarks while generalizing across 2D and 3D data.
Sita: Single image test-time adaptation,
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Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation
TopoTTA integrates persistent homology into test-time adaptation to derive topological pseudo-labels from anomaly maps, improving segmentation by an average 15% F1 on six benchmarks while generalizing across 2D and 3D data.