“Faceshop: deep sketch-based face image editing” by Portenier, Hu, Szabo, Bigdeli, Favaro, et al. …

  • ©Tiziano Portenier, Qiyang Hu, Attila Szabo, Siavash Arjomand Bigdeli, Paolo Favaro, and Matthias Zwicker



Entry Number: 99


    Faceshop: deep sketch-based face image editing

Session/Category Title: Sketching




    We present a novel system for sketch-based face image editing, enabling users to edit images intuitively by sketching a few strokes on a region of interest. Our interface features tools to express a desired image manipulation by providing both geometry and color constraints as user-drawn strokes. As an alternative to the direct user input, our proposed system naturally supports a copy-paste mode, which allows users to edit a given image region by using parts of another exemplar image without the need of hand-drawn sketching at all. The proposed interface runs in real-time and facilitates an interactive and iterative workflow to quickly express the intended edits. Our system is based on a novel sketch domain and a convolutional neural network trained end-to-end to automatically learn to render image regions corresponding to the input strokes. To achieve high quality and semantically consistent results we train our neural network on two simultaneous tasks, namely image completion and image translation. To the best of our knowledge, we are the first to combine these two tasks in a unified framework for interactive image editing. Our results show that the proposed sketch domain, network architecture, and training procedure generalize well to real user input and enable high quality synthesis results without additional post-processing.


    1. Connelly Barnes, Eli Shechtman, Adam Finkelstein, and Dan B Goldman. 2009. Patch-Match: A Randomized Correspondence Algorithm for Structural Image Editing. ACM Transactions on Graphics (Proc. SIGGRAPH) 28, 3 (Aug. 2009). Google ScholarDigital Library
    2. Marcelo Bertalmio, Guillermo Sapiro, Vincent Caselles, and Coloma Ballester. 2000. Image Inpainting. In Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH ’00). ACM Press/Addison-Wesley Publishing Co., New York, NY, USA, 417–424. Google ScholarDigital Library
    3. Marcelo Bertalmio, Luminita Vese, Guillermo Sapiro, and Stanley Osher. 2003. Simultaneous structure and texture image inpainting. IEEE Transactions on image processing 12, 8 (2003), 882–889. Google ScholarDigital Library
    4. David Berthelot, Tom Schumm, and Luke Metz. 2017. BEGAN: Boundary Equilibrium Generative Adversarial Networks. CoRR abs/1703.10717 (2017). arXiv:1703.10717 http://arxiv.org/abs/1703.10717Google Scholar
    5. Qifeng Chen and Vladlen Koltun. 2017. Photographic Image Synthesis With Cascaded Refinement Networks. In The IEEE International Conference on Computer Vision (ICCV).Google Scholar
    6. Antonio Criminisi, Patrick Pérez, and Kentaro Toyama. 2004. Region filling and object removal by exemplar-based image inpainting. IEEE Transactions on image processing 13, 9 (2004), 1200–1212. Google ScholarDigital Library
    7. Soheil Darabi, Eli Shechtman, Connelly Barnes, Dan B Goldman, and Pradeep Sen. 2012. Image Melding: Combining Inconsistent Images using Patch-based Synthesis. ACM Transactions on Graphics (TOG) (Proceedings of SIGGRAPH 2012) 31, 4, Article 82 (2012), 82:1–82:10 pages. Google ScholarDigital Library
    8. Brian Dolhansky and Cristian Canton Ferrer. 2017. Eye In-Painting with Exemplar Generative Adversarial Networks. arXiv preprint arXiv:1712.03999 (2017).Google Scholar
    9. Iddo Drori, Daniel Cohen-Or, and Hezy Yeshurun. 2003. Fragment-based image completion. In ACM Transactions on graphics (TOG), Vol. 22. ACM, 303–312. Google ScholarDigital Library
    10. Alexei A. Efros and William T. Freeman. 2001. Image Quilting for Texture Synthesis and Transfer. In Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH ’01). ACM, New York, NY, USA, 341–346. Google ScholarDigital Library
    11. Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. 2015. A Neural Algorithm of Artistic Style. CoRR abs/1508.06576 (2015). arXiv:1508.06576 http://arxiv.org/abs/1508.06576Google Scholar
    12. Michaël Gharbi, Jiawen Chen, Jonathan T Barron, Samuel W Hasinoff, and Frédo Durand. 2017. Deep bilateral learning for real-time image enhancement. ACM Transactions on Graphics (TOG) 36, 4 (2017), 118. Google ScholarDigital Library
    13. Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative Adversarial Nets. In Advances in Neural Information Processing Systems 27, Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, and K. Q. Weinberger (Eds.). Curran Associates, Inc., 2672–2680. http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf Google ScholarDigital Library
    14. Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville. 2017. Improved Training of Wasserstein GANs. In Advances in Neural Information Processing Systems 30, 1. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.). Curran Associates, Inc., 5769–5779. http://papers.nips.cc/paper/7159-improved-training-of-wasserstein-gans.pdfGoogle Scholar
    15. Satoshi Iizuka, Edgar Simo-Serra, and Hiroshi Ishikawa. 2016. Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification. ACM Transactions on Graphics (Proc. of SIGGRAPH 2016) 35, 4 (2016), 110:1–110:11. Google ScholarDigital Library
    16. Satoshi Iizuka, Edgar Simo-Serra, and Hiroshi Ishikawa. 2017. Globally and Locally Consistent Image Completion. ACM Transactions on Graphics (Proc. of SIGGRAPH 2017) 36, 4, Article 107 (2017), 107:1–107:14 pages. Google ScholarDigital Library
    17. Instagram. 2018. Instagram Press. (2018). https://instagram-press.com/Google Scholar
    18. Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros. 2017. Image-To-Image Translation With Conditional Adversarial Networks. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Google Scholar
    19. Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen. 2017. Progressive Growing of GANs for Improved Quality, Stability, and Variation. CoRR abs/1710.10196 (2017). arXiv:1710.10196 http://arxiv.org/abs/1710.10196Google Scholar
    20. Ira Kemelmacher-Shlizerman. 2016. Transfiguring Portraits. ACM Trans. Graph. 35, 4, Article 94 (July 2016), 8 pages. Google ScholarDigital Library
    21. Diederik P. Kingma and Jimmy Ba. 2014. Adam: A Method for Stochastic Optimization. CoRR abs/1412.6980 (2014). arXiv:1412.6980 http://arxiv.org/abs/1412.6980Google Scholar
    22. Yijun Li, Sifei Liu, Jimei Yang, and Ming-Hsuan Yang. 2017. Generative Face Completion. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Google Scholar
    23. Jing Liao, Yuan Yao, Lu Yuan, Gang Hua, and Sing Bing Kang. 2017. Visual Attribute Transfer Through Deep Image Analogy. ACM Trans. Graph. 36, 4, Article 120 (July 2017), 15 pages. Google ScholarDigital Library
    24. Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang. 2015. Deep Learning Face Attributes in the Wild. In Proceedings of International Conference on Computer Vision (ICCV). Google ScholarDigital Library
    25. Mehdi Mirza and Simon Osindero. 2014. Conditional Generative Adversarial Nets. CoRR abs/1411.1784 (2014). arXiv:1411.1784 http://arxiv.org/abs/1411.1784Google Scholar
    26. Deepak Pathak, Philipp Krähenbühl, Jeff Donahue, Trevor Darrell, and Alexei Efros. 2016. Context Encoders: Feature Learning by Inpainting.Google Scholar
    27. Patrick Pérez, Michel Gangnet, and Andrew Blake. 2003. Poisson Image Editing. ACM Trans. Graph. 22, 3 (July 2003), 313–318. Google ScholarDigital Library
    28. Patsorn Sangkloy, Jingwan Lu, Chen Fang, Fisher Yu, and James Hays. 2017. Scribbler: Controlling Deep Image Synthesis with Sketch and Color. Computer Vision and Pattern Recognition, CVPR (2017).Google Scholar
    29. Ahmed Selim, Mohamed Elgharib, and Linda Doyle. 2016. Painting Style Transfer for Head Portraits Using Convolutional Neural Networks. ACM Trans. Graph. 35, 4, Article 129 (July 2016), 18 pages. Google ScholarDigital Library
    30. Jianhong Shen and Tony F. Chan. 2002. Mathematical Models for Local Nontexture Inpaintings. SIAM J. Appl. Math. 62, 3 (2002), 1019–1043.Google ScholarDigital Library
    31. Fabian Timm and Erhardt Barth. 2011. Accurate Eye Centre Localisation by Means of Gradients. Visapp 11 (2011), 125–130.Google Scholar
    32. Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz, and Bryan Catanzaro. 2017. High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs. arXiv preprint arXiv:1711.11585 (2017).Google Scholar
    33. Martin Weber. 2018. AutoTrace. (2018). http://autotrace.sourceforge.net/Google Scholar
    34. Saining Xie and Zhuowen Tu. 2015. Holistically-Nested Edge Detection. In The IEEE International Conference on Computer Vision (ICCV). Google ScholarDigital Library
    35. Zhicheng Yan, Hao Zhang, Baoyuan Wang, Sylvain Paris, and Yizhou Yu. 2016. Automatic Photo Adjustment Using Deep Neural Networks. ACM Trans. Graph. 35, 2, Article 11 (2016), 15 pages. Google ScholarDigital Library
    36. Raymond A. Yeh, Chen Chen, Teck Yian Lim, Alexander G. Schwing, Mark Hasegawa-Johnson, and Minh N. Do. 2017. Semantic Image Inpainting With Deep Generative Models. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Google Scholar
    37. Fisher Yu and Vladlen Koltun. 2016. Multi-Scale Context Aggregation by Dilated Convolutions. In ICLR.Google Scholar
    38. Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S Lin, Tianhe Yu, and Alexei A Efros. 2017. Real-Time User-Guided Image Colorization with Learned Deep Priors. ACM Transactions on Graphics (TOG) 9, 4 (2017). Google ScholarDigital Library
    39. Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A. Efros. 2017. Unpaired Image-to-image Translation using Cycle-Consistent Adversarial Networks. CoRR abs/1703.10593 (2017). arXiv:1703.10593 http://arxiv.org/abs/1703.10593Google Scholar

ACM Digital Library Publication:

Overview Page: