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Paint2Pix: Interactive Painting Based Progressive Image Synthesis and Editing

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Computer Vision – ECCV 2022 (ECCV 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13674))

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Abstract

Controllable image synthesis with user scribbles is a topic of keen interest in the computer vision community. In this paper, for the first time we study the problem of photorealistic image synthesis from incomplete and primitive human paintings. In particular, we propose a novel approach paint2pix, which learns to predict (and adapt) “what a user wants to draw” from rudimentary brushstroke inputs, by learning a mapping from the manifold of incomplete human paintings to their realistic renderings. When used in conjunction with recent works in autonomous painting agents, we show that paint2pix can be used for progressive image synthesis from scratch. During this process, paint2pix allows a novice user to progressively synthesize the desired image output, while requiring just few coarse user scribbles to accurately steer the trajectory of the synthesis process. Furthermore, we find that our approach also forms a surprisingly convenient approach for real image editing, and allows the user to perform a diverse range of custom fine-grained edits through the addition of only a few well-placed brushstrokes. Source code and demo is available at https://github.com/1jsingh/paint2pix.

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Author information

Authors and Affiliations

  1. Australian National University, Canberra, Australia

    Jaskirat Singh & Liang Zheng

  2. Adobe Research, San Jose, USA

    Jaskirat Singh, Cameron Smith & Jose Echevarria

Authors
  1. Jaskirat Singh
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  2. Liang Zheng
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  3. Cameron Smith
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  4. Jose Echevarria
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Corresponding author

Correspondence to Jaskirat Singh .

Editor information

Editors and Affiliations

  1. Tel Aviv University, Tel Aviv, Israel

    Shai Avidan

  2. University College London, London, UK

    Gabriel Brostow

  3. Google AI, Accra, Ghana

    Moustapha Cissé

  4. University of Catania, Catania, Italy

    Giovanni Maria Farinella

  5. Facebook (United States), Menlo Park, CA, USA

    Tal Hassner

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Singh, J., Zheng, L., Smith, C., Echevarria, J. (2022). Paint2Pix: Interactive Painting Based Progressive Image Synthesis and Editing. In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T. (eds) Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol 13674. Springer, Cham. https://doi.org/10.1007/978-3-031-19781-9_39

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  • DOI: https://doi.org/10.1007/978-3-031-19781-9_39

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