Semi-Supervised Sketch Based Image Retrieval

Semi-Supervised Sketch-Based Image Retrieval is a research direction in the field of computer vision, aiming to leverage large amounts of unlabeled photo data to enhance the performance of fine-grained sketch-based image retrieval. This task explores how to effectively utilize rich unlabeled image resources under limited annotated data, thereby breaking through the upper limit of sketch data volume and improving the accuracy and robustness of the retrieval system. Its application value lies in achieving efficient and precise sketch matching and retrieval in large-scale image libraries, suitable for cross-modal image search, content creation assistance, and other scenarios.