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We advance sketch research to scenes with the first dataset of freehand scenesketches, FS-COCO. With practical applications in mind, we collect sketchesthat convey scene content well but can be sketched within a few minutes by aperson with any sketching skills. Our dataset comprises 10,000 freehand scenevector sketches with per point space-time information by 100 non-expertindividuals, offering both object- and scene-level abstraction. Each sketch isaugmented with its text description. Using our dataset, we study for the firsttime the problem of fine-grained image retrieval from freehand scene sketchesand sketch captions. We draw insights on: (i) Scene salience encoded insketches using the strokes temporal order; (ii) Performance comparison of imageretrieval from a scene sketch and an image caption; (iii) Complementarity ofinformation in sketches and image captions, as well as the potential benefit ofcombining the two modalities. In addition, we extend a popular vector sketchLSTM-based encoder to handle sketches with larger complexity than was supportedby previous work. Namely, we propose a hierarchical sketch decoder, which weleverage at a sketch-specific "pre-text" task. Our dataset enables for thefirst time research on freehand scene sketch understanding and its practicalapplications.

FS-COCO: Towards Understanding of Freehand Sketches of Common Objects in Context