LA-Sign achieves state-of-the-art skeleton-based sign language recognition on WLASL and MSASL by using recurrent looped transformers with adaptive hyperbolic geometry alignment.
Advances in neural information processing systems31(2018)
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Hyp2Former learns hierarchical semantic similarities in hyperbolic space among known categories so that unknown objects remain close to higher-level concepts and can be detected reliably.
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LA-Sign: Looped Transformers with Geometry-aware Alignment for Skeleton-based Sign Language Recognition
LA-Sign achieves state-of-the-art skeleton-based sign language recognition on WLASL and MSASL by using recurrent looped transformers with adaptive hyperbolic geometry alignment.
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Hyp2Former: Hierarchy-Aware Hyperbolic Embeddings for Open-Set Panoptic Segmentation
Hyp2Former learns hierarchical semantic similarities in hyperbolic space among known categories so that unknown objects remain close to higher-level concepts and can be detected reliably.