Sign Language Retrieval

Sign language retrieval focuses on developing systems that can efficiently search and retrieve video clips of signed language based on textual queries or similarity to other videos. Current research emphasizes improving the accuracy and efficiency of retrieval by leveraging multimodal approaches (combining visual and pose data), developing sophisticated embedding techniques (like contrastive learning and probability distribution modeling), and addressing data scarcity through techniques such as pseudo-labeling and iterative data augmentation. These advancements are crucial for improving accessibility to information for the Deaf community and advancing the field of sign language processing.