Semi-Supervised Sketch Based Image Retrieval
1 papers with code • 0 benchmarks • 0 datasets
Whilst the number of photos can be easily scaled, each corresponding sketch still needs to be individually produced for fine-grained sketch-based image retrieval. The objective is to mitigate such an upper-bound on sketch data, and study whether unlabelled photos alone (of which they are many) can be cultivated for performance gain.
These leaderboards are used to track progress in Semi-Supervised Sketch Based Image Retrieval
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval
A fundamental challenge faced by existing Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) models is the data scarcity -- model performances are largely bottlenecked by the lack of sketch-photo pairs.