SignMAE: Segmentation-Driven Self-Supervised Learning for Sign Language Recognition
arXiv:2605.02094v1 Announce Type: new
Abstract: Subtle hand differences make sign language recognition challenging, yet many existing methods rely on encoders pretrained on generic action datasets that poorly capture such fine-grained cues. We propose…