mlsanityData to 14 Oct 2026

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

arXiv 2108.07353 ↗First posted 16 Aug 2021cs.CVcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 18 of its 33 references that are in the map. First posted on arXiv 16 Aug 2021.

Builds on

18 of 33 references.

References · 18

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  12. 2018Image Generation from Scene Graphscited by 324
6 more
  1. 2018SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesiscited by 81
  2. 2020Sketchformer: Transformer-based Representation for Sketched Structurecited by 78
  3. 2020SketchyCOCO: Image Generation from Freehand Scene Sketchescited by 67
  4. 2015Sketch-based 3D Shape Retrieval using Convolutional Neural Networkscited by 41
  5. 2017Image Generation from Sketch Constraint Using Contextual GANcited by 34
  6. 2019Aligning Linguistic Words and Visual Semantic Units for Image Captioningcited by 25

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 0; 2026: 1.

3 papers.