Back To The Drawing Board: Rethinking Scene-Level Sketch-Based Image Retrieval


Emil Demić (University of Ljubljana), Luka Čehovin Zajc (University of Ljubljana)
The 35th British Machine Vision Conference
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Abstract

The goal of Scene-level Sketch-Based Image Retrieval is to retrieve natural images matching the overall semantics and spatial layout of a free-hand sketch. Unlike prior work focused on architectural augmentations of retrieval models, we emphasize the inherent ambiguity and noise present in real-world sketches. This insight motivates a training objective that is explicitly designed to be robust to sketch variability. We show that with an appropriate combination of pre-training, encoder architecture, and loss formulation, it is possible to achieve state-of-the-art performance without the introduction of additional complexity. Extensive experiments on a challenging FS-COCO and widely-used SketchyCOCO datasets confirm the effectiveness of our approach and underline the critical role of training design in cross-modal retrieval tasks, as well as the need to improve the evaluation scenarios of scene-level SBIR.

Citation

@inproceedings{Demić_2025_BMVC,
author    = {Emil Demić and Luka Čehovin Zajc},
title     = {Back To The Drawing Board: Rethinking Scene-Level Sketch-Based Image Retrieval},
booktitle = {36th British Machine Vision Conference 2025, {BMVC} 2025, Sheffield, UK, November 24-27, 2025},
publisher = {BMVA},
year      = {2025},
url       = {https://bmva-archive.org.uk/bmvc/2025/assets/papers/Paper_373/paper.pdf}
}


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