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We present CoGS, a novel method for the style-conditioned, sketch-driven synthesis of images.
1905
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Tian, Y., Krishnan, D., Isola, P.: Contrastive multiview coding. CoRR abs/1906.05849
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Wexler, Y., Shechtman, E., Irani, M.: Space-time video completion. In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. vol. 1, pp. I–I. IEEE (2004)
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Hays, J., Efros, A.A.: Scene completion using millions of photographs. ACM Transactions on Graphics (TOG) 26
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Collomosse, J.P., McNeill, G., Watts, L.: Free-hand sketch grouping for video retrieval. In: Proc. ICPR (2008)
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Barnes, C., Shechtman, E., Finkelstein, A., Goldman, D.B.: Patchmatch: A randomized correspondence algorithm for structural image editing. ACM Transactions on Graphics (ToG) 28
2009
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Chen, T., Cheng, M.M., Tan, P., Shamir, A., Hu, S.M.: Sketch2photo: Internet image montage. Proc. ACM SIGGRAPH 28
2009
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Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: A large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition. pp. 248–255. Ieee (2009)
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Eitz, M., Hays, J., Alexa, M.: How do humans sketch objects? ACM Trans. Graph. (Proc. SIGGRAPH) 31
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Kingma, D.P., Welling, M.: Auto-Encoding Variational Bayes. ArXiv e-prints (Dec 2013)
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Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., Abbeel, P.: Infogan: Interpretable representation learning by information maximizing generative adversarial nets (Jun 2016)
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Gatys, L.A., Ecker, A.S., Bethge, M.: Image style transfer using convolutional neural networks. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 2414–2423 (2016). https://doi.org/10.1109/CVPR.2016.265
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Gucluturk, Y., Guclu, U., van Lier, R., van Gerven, M.A.: Convolutional sketch inversion. In: Proc. ECCV Workshop on Vision and Art (VISART) (2016)
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Hospedales, T., Song, Y.Z.: Sketch me that shoe (01 2016)
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Iizuka, S., Simo-Serra, E., Ishikawa, H.: 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
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Jongejan, J., Rowley, H., Kawashima, T., Kim, J., Fox-Gieg, N.: The quick, draw! a.i. experiment (2016), https://quickdraw.withgoogle.com/
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Reed, S., Akata, Z., Mohan, S., Tenka, S., Schiele, B., Lee, H.: Learning what and where to draw. In: Advances in Neural Information Processing Systems (NIPS) (2016)
2016
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Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., Lee, H.: Generative adversarial text-to-image synthesis. In: Proc. ICML (2016)
2016
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Sangkloy, P., Burnell, N., Ham, C., Hays, J.: The sketchy database: learning to retrieve badly drawn bunnies. ACM Transactions on Graphics (TOG) 35
2016
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Sangkloy, P., Burnell, N., Ham, C., Hays, J.: The sketchy database: Learning to retrieve badly drawn bunnies. ACM Trans. Graph. 35
2016
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Song, J., Song, Y.Z., Xiang, T., Hospedales, T., Ruan, X.: Deep multi-task attribute-driven ranking for fine-grained sketch-based image retrieval. In: British Machine Vision Conference (2016)
Inoue, N., Ito, D., Xu, N., Yang, J., Price, B., Yamasaki, T.: Learning to trace: Expressive line drawing generation from photographs. Computer Graphics Forum 38
2019
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Park, T., Liu, M.Y., Wang, T.C., Zhu, J.Y.: Semantic image synthesis with spatially-adaptive normalization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2019)
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Sun, W., Wu, T.: Image synthesis from reconfigurable layout and style. In: Proc. CVPR (2019)
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2019
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Zhao, B., Meng, L., Yin, W., Sigal, L.: Image generation from layout. In: Proc. CVPR (2019)
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2016
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Zhu, J.Y., Krahenbuhl, P., Shechtman, E., Efros, A.A.: Generative visual manipulation on the natural image manifold. In: Proc. ECCV (2016)
2016
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Barnes, C., Zhang, F.L.: A survey of the state-of-the-art in patch-based synthesis. Computational Visual Media 3
2017
Cited alongside, same era.
Collomosse, J., Bui, T., Wilber, M., Fang, C., Jin, H.: Sketching with style: Visual search with sketches and aesthetic context. In: Proc. ICCV (2017)
2017
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Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: Gans trained by a two time-scale update rule converge to a local nash equilibrium. Advances in neural information processing systems 30
2017
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Isola, P., Zhu, J., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 5967–5976 (2017). https://doi.org/10.1109/CVPR.2017.632
2017
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Sangkloy, P., Lu, J., Fang, C., Yu, F., Hays, J.: Scribbler: Controlling deep image synthesis with sketch and color. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 5400–5409 (2017)
2017
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Song, J., Yu, Q., Song, Y.Z., Xiang, T., Hospedales, T.M.: Deep spatial-semantic attention for fine-grained sketch-based image retrieval. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV) (Oct 2017)
2017
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2019
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Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: III, H.D., Singh, A. (eds.) Proceedings of the 37th International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 119, pp. 1597–1607. PMLR (13–18 Jul 2020), https://proceedings.mlr.press/v119/chen20j.html
2020
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2020
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Esser, P., Rombach, R., Ommer, B.: Taming transformers for high-resolution image synthesis (2020)
2020
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Gao, C., Liu, Q., Xu, Q., Wang, L., Liu, J., Zou, C.: Sketchycoco: Image generation from freehand scene sketches. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (June 2020)
2020
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Gao, H., Chen, Z., Huang, B., Chen, J., Li, Z.: Image super-resolution based on conditional generative adversarial network. IET Image Processing 14
2020
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Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., Aila, T.: Analyzing and improving the image quality of StyleGAN. In: Proc. CVPR (2020)
2020
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Ribeiro, L.S.F., Bui, T., Collomosse, J., Ponti, M.: Sketchformer: Transformer-based representation for sketched structure. In: Proc. CVPR (2020)
2020
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2020
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2020
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2021
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Guo, X., Yang, H., Huang, D.: Image inpainting via conditional texture and structure dual generation (2021)
2021
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Huang, X., Mallya, A., Wang, T.C., Liu, M.Y.: Multimodal conditional image synthesis with product-of-experts gans (2021)
2021
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2021
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2021
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Ribeiro, L., Bui, T., Collomosse, J., Ponti, M.: Scene designer: a unified model for scene search and synthesis from sketch. In: Proc. CVPRW on Sketch and Human Expressivity (SHE) (2021)
2021
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Ruta, D., Motiian, S., Faieta, B., Lin, Z.L., Jin, H., Filipkowski, A., Gilbert, A., Collomosse, J.P.: Aladin: All layer adaptive instance normalization for fine-grained style similarity. 2021 IEEE/CVF International Conference on Computer Vision (ICCV) pp. 11906–11915 (2021)
2021
Later among the works it cites.
Xue, Y., Guo, Y.C., Zhang, H., Xu, T., Zhang, S.H., Huang, X.: Deep image synthesis from intuitive user input: A review and perspectives. Computational Visual Media 8
2022
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