Sign Retrieval

Sign retrieval focuses on efficiently representing and retrieving information from sign language videos, aiming to overcome challenges posed by the complex visual and semantic nature of signed communication. Current research emphasizes multimodal approaches, integrating pose estimation data with RGB video to capture both fine-grained hand movements and broader contextual information, often employing deep learning architectures like dual-stream encoders with attention mechanisms for improved feature fusion and semantic understanding. These advancements are crucial for improving accessibility to sign language resources and enabling applications such as automated sign language translation and video summarization, ultimately bridging communication gaps for the Deaf community.