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September 12, 2025PeerJ Computer ScienceOpen Access

SignVLM: a pre-trained large video model for sign language recognition

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The proposed model SignVLM improved sign language recognition accuracy on multiple datasets.
Evaluation indicated strong performance in zero-shot and few-shot learning scenarios for sign language recognition.
Using a combination of the CLIP model and Transformer decoder, spatial and temporal features were effectively learned.
The model showed promising generalization abilities to new datasets, ensuring robustness in low-resourced sign languages.

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This research demonstrates SignVLM's effectiveness in recognizing sign language gestures, indicating its potential for broader application.

Hamzah Luqman (2025) studied this question.

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This research demonstrates SignVLM's effectiveness in recognizing sign language gestures, indicating its potential for broader application.