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Zero Shot Skeletal Action Recognition On Ntu

Métriques

Accuracy (12 unseen classes)

Accuracy (5 unseen classes)

Random Split Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy (12 unseen classes)	Accuracy (5 unseen classes)	Random Split Accuracy	Paper Title	Repository
SA-DVAE	41.38	82.37	84.20	SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders	-
SA-DVAE + augmented text	-	-	87.61	SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders	-
PURLS	40.99	79.23	-	Part-aware Unified Representation of Language and Skeleton for Zero-shot Action Recognition
STAR	45.10	81.40	77.50	Fine-Grained Side Information Guided Dual-Prompts for Zero-Shot Skeleton Action Recognition	-
TDSM	56.03	86.49	88.88	TDSM: Triplet Diffusion for Skeleton-Text Matching in Zero-Shot Action Recognition
SMIE	40.18	77.98	65.08	Zero-shot Skeleton-based Action Recognition via Mutual Information Estimation and Maximization
CADA-VAE	28.96	76.84	60.74	Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders
SynSE	33.30	75.81	64.19	Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action Recognition

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