Continuous Sign Language Recognition

Continuous Sign Language Recognition (CSLR) aims to automatically translate continuous sign language videos into text, bridging communication gaps between deaf and hearing communities. Current research heavily utilizes deep learning, focusing on transformer-based architectures and multimodal approaches that integrate visual information from hands, face, and body, often incorporating attention mechanisms to improve feature extraction and temporal modeling. Efforts are underway to improve robustness to real-world conditions like varied backgrounds and lighting, and to develop more efficient models for real-time applications. Advances in CSLR have significant implications for accessibility, enabling improved communication tools and potentially impacting sign language education and research.