Semantic Adversarial Network for Zero-Shot Sketch-Based Image Retrieval

Understand

Zero-shot sketch-based image retrieval (ZS-SBIR) is a specific cross-modal retrieval task for retrieving natural images with free-hand sketches under zero-shot scenario.

• Previous works mostly focus on modeling the correspondence between images and sketches or synthesizing image features with sketch features.
• However, both of them ignore the large intra-class variance of sketches, thus resulting in unsatisfactory retrieval performance.
• In this paper, we propose a novel end-to-end semantic adversarial approach for ZS-SBIR.