H-SPAM produces accurate, regular, and perfectly nested hierarchical superpixels that outperform prior hierarchical methods and match recent non-hierarchical state-of-the-art.
In: CVPR (2021)
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CV 2years
2026 2representative citing papers
Self-supervised cross-modal contrastive learning coordinates plankton image and profile data to enable accurate species recognition from minimal labeled images.
citing papers explorer
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H-SPAM: Hierarchical Superpixel Anything Model
H-SPAM produces accurate, regular, and perfectly nested hierarchical superpixels that outperform prior hierarchical methods and match recent non-hierarchical state-of-the-art.
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Cross-modal learning for plankton recognition
Self-supervised cross-modal contrastive learning coordinates plankton image and profile data to enable accurate species recognition from minimal labeled images.