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Sebastian Hartwig

1 accepted papers

2025

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation

ICCV 2025poster

Traditionally, algorithms that learn to segment object instances in 2D images have heavily relied on large amounts of human-annotated data. Only recently, novel approaches have emerged tackling this problem in an unsupervised fashion. Generally, these approaches first generate pseudo-masks and then…

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