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Found 4 papers, 2 papers with code
Natural Language-Assisted Sign Language Recognition
Sign languages are visual languages which convey information by signers' handshape, facial expression, body movement, and so forth.
Ranked #1 on
Sign Language Recognition
on WLASL-2000
Improving Continuous Sign Language Recognition with Consistency Constraints and Signer Removal
We name the CSLR model trained with the above auxiliary tasks as consistency-enhanced CSLR, which performs well on signer-dependent datasets in which all signers appear during both training and testing.
Ranked #7 on
Sign Language Recognition
on CSL-Daily
Two-Stream Network for Sign Language Recognition and Translation
RGB videos, however, are raw signals with substantial visual redundancy, leading the encoder to overlook the key information for sign language understanding.
C2SLR: Consistency-Enhanced Continuous Sign Language Recognition
The backbone of most deep-learning-based continuous sign language recognition (CSLR) models consists of a visual module, a sequential module, and an alignment module.
