Papers › Scene Designer: a Unified Model for Scene Search and Synthesis from Sketch

Scene Designer: a Unified Model for Scene Search and Synthesis from Sketch

16 Aug 2021arXiv:2108.07353archive 2025-07-28

Leo Sampaio Ferraz Ribeiro, Tu Bui, John Collomosse, Moacir Ponti

Scene Designer is a novel method for searching and generating images using free-hand sketches of scene compositions; i.e. drawings that describe both the appearance and relative positions of objects. Our core contribution is a single unified model to learn both a cross-modal search embedding for matching sketched compositions to images, and an object embedding for layout synthesis. We show that a graph neural network (GNN) followed by Transformer under our novel contrastive learning setting is required to allow learning correlations between object type, appearance and arrangement, driving a mask generation module that synthesises coherent scene layouts, whilst also delivering state of the art sketch based visual search of scenes.

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Contrastive LearningGraph Neural NetworkObject

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Absolute Position EncodingsAdamAttentionBPEContrastive LearningDense ConnectionsDropoutGraph Neural NetworkLabel SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSoftmaxTransformer

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