Fine Grained Sketch

Fine-grained sketch-based image retrieval (FG-SBIR) focuses on accurately matching detailed sketches to corresponding images, a challenging task due to the abstract and variable nature of sketches. Current research emphasizes improving retrieval accuracy through multimodal learning approaches, leveraging the synergy between visual and textual information from models like CLIP, and developing self-supervised methods to generate larger, more diverse sketch datasets. These advancements aim to enhance the practicality of sketch-based applications in various fields, including image generation, 3D model retrieval, and interactive visual interfaces, by bridging the semantic gap between sketches and photos. The development of robust and efficient FG-SBIR models is crucial for enabling more intuitive and user-friendly interactions with digital visual information.