Fetching the paper…
Reading the bibliography…
Deep generative models have become increasingly effective at producing realistic images from randomly sampled seeds, but using such models for controllable manipulation of existing images remains challenging.
Julesz, B.: Visual pattern discrimination. IRE transactions on Information Theory
1962
Earlier work this paper cites.
Julesz, B., Gilbert, E.N., Shepp, L.A., Frisch, H.L.: Inability of humans to discriminate between visual textures that agree in second-order statistics—revisited. Perception
1973
Earlier work this paper cites.
Julesz, B.: Textons, the elements of texture perception, and their interactions. Nature
1981
Earlier work this paper cites.
Heeger, D.J., Bergen, J.R.: Pyramid-based texture analysis/synthesis. In: Proceedings of the 22nd annual conference on Computer graphics and interactive techniques. pp. 229–238 (1995)
1995
Earlier work this paper cites.
Portilla, J., Simoncelli, E.P.: A parametric texture model based on joint statistics of complex wavelet coefficients. International journal of computer vision
2000
Earlier work this paper cites.
Tenenbaum, J.B., Freeman, W.T.: Separating style and content with bilinear models. Neural computation
2000
Earlier work this paper cites.
Hertzmann, A., Jacobs, C.E., Oliver, N., Curless, B., Salesin, D.H.: Image analogies. In: ACM Transactions on Graphics (TOG) (2001)
2001
Earlier work this paper cites.
Hinton, G.E., Salakhutdinov, R.R.: Reducing the dimensionality of data with neural networks. Science
2006
Earlier work this paper cites.
Salakhutdinov, R., Hinton, G.: Deep boltzmann machines. In: Artificial intelligence and statistics. pp. 448–455 (2009)
2009
Earlier work this paper cites.
Bengio, Y.: Deep learning of representations: Looking forward. In: International Conference on Statistical Language and Speech Processing (2013)
2013
Earlier work this paper cites.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: Advances in Neural Information Processing Systems (2014)
2014
Earlier work this paper cites.
Kingma, D.P., Welling, M.: Auto-encoding variational bayes. In: International Conference on Learning Representations (ICLR) (2014)
2014
Earlier work this paper cites.
Gatys, L., Ecker, A.S., Bethge, M.: Texture synthesis using convolutional neural networks. In: Advances in Neural Information Processing Systems (2015)
2015
Earlier work this paper cites.
Ioffe, S., Szegedy, C.: Batch normalization: Accelerating deep network training by reducing internal covariate shift. In: International Conference on Machine Learning (ICML) (2015)
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. In: International Conference on Learning Representations (ICLR) (2015)
2015
Earlier work this paper cites.
Liu, Z., Luo, P., Wang, X., Tang, X.: Deep learning face attributes in the wild. In: IEEE International Conference on Computer Vision (ICCV) (2015)
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., Abbeel, P.: Infogan: Interpretable representation learning by information maximizing generative adversarial nets. In: Advances in Neural Information Processing Systems (2016)
2016
Earlier work this paper cites.
Dosovitskiy, A., Brox, T.: Generating images with perceptual similarity metrics based on deep networks. In: Advances in Neural Information Processing Systems (2016)
2016
Earlier work this paper cites.
Farid, H.: Photo forensics. MIT press (2016)
2016
Earlier work this paper cites.
Gatys, L.A., Ecker, A.S., Bethge, M.: Image style transfer using convolutional neural networks. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
2016
Earlier work this paper cites.
He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
2016
Earlier work this paper cites.
Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: European Conference on Computer Vision (ECCV) (2016)
2016
Earlier work this paper cites.
Larsson, G., Maire, M., Shakhnarovich, G.: Learning representations for automatic colorization. In: European Conference on Computer Vision (ECCV) (2016)
2016
Earlier work this paper cites.
Lin, T.Y., Maji, S.: Visualizing and understanding deep texture representations. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 2791–2799 (2016)
2016
Earlier work this paper cites.
Mathieu, M.F., Zhao, J.J., Zhao, J., Ramesh, A., Sprechmann, P., LeCun, Y.: Disentangling factors of variation in deep representation using adversarial training. In: Advances in Neural Information Processing Systems (2016)
2016
Earlier work this paper cites.
Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., Efros, A.A.: Context encoders: Feature learning by inpainting. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
2016
Earlier work this paper cites.
Perarnau, G., van de Weijer, J., Raducanu, B., Álvarez, J.M.: Invertible conditional gans for image editing. In: NIPS Workshop on Adversarial Training (2016)
2016
Earlier work this paper cites.
Ulyanov, D., Lebedev, V., Vedaldi, A., Lempitsky, V.: Texture networks: Feed-forward synthesis of textures and stylized images. In: International Conference on Machine Learning (ICML) (2016)
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
Zhang, R., Isola, P., Efros, A.A.: Colorful image colorization. In: European Conference on Computer Vision (ECCV) (2016)
2016
Earlier work this paper cites.
Zhu, J.Y., Krähenbühl, P., Shechtman, E., Efros, A.A.: Generative visual manipulation on the natural image manifold. In: European Conference on Computer Vision (ECCV) (2016)
2016
Cited alongside, same era.
Brock, A., Lim, T., Ritchie, J.M., Weston, N.: Neural photo editing with introspective adversarial networks. In: International Conference on Learning Representations (ICLR) (2017)
2017
Cited alongside, same era.
Chen, D., Yuan, L., Liao, J., Yu, N., Hua, G.: Stylebank: An explicit representation for neural image style transfer. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 1897–1906 (2017)
2017
Cited alongside, same era.
Chen, Q., Koltun, V.: Photographic image synthesis with cascaded refinement networks. In: IEEE International Conference on Computer Vision (ICCV) (2017)
2017
Cited alongside, same era.
Wang, T.C., Liu, M.Y., Zhu, J.Y., Tao, A., Kautz, J., Catanzaro, B.: High-resolution image synthesis and semantic manipulation with conditional gans. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
2018
Later among the works it cites.
Xian, W., Sangkloy, P., Agrawal, V., Raj, A., Lu, J., Fang, C., Yu, F., Hays, J.: Texturegan: Controlling deep image synthesis with texture patches. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
2018
Later among the works it cites.
Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., Huang, T.S.: Generative image inpainting with contextual attention. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2018)
2018
Later among the works it cites.
Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Dinh, L., Sohl-Dickstein, J., Bengio, S.: Density estimation using real nvp. In: International Conference on Learning Representations (ICLR) (2017)
2017
Cited alongside, same era.
Guérin, E., Digne, J., Galin, E., Peytavie, A., Wolf, C., Benes, B., Martinez, B.: Interactive example-based terrain authoring with conditional generative adversarial networks. ACM Transactions on Graphics (TOG)
2017
Cited alongside, same era.
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. In: Advances in Neural Information Processing Systems (2017)
2017
Cited alongside, same era.
Higgins, I., Matthey, L., Pal, A., Burgess, C., Glorot, X., Botvinick, M., Mohamed, S., Lerchner, A.: beta-vae: Learning basic visual concepts with a constrained variational framework. In: International Conference on Learning Representations (ICLR) (2017)
2017
Cited alongside, same era.
Iizuka, S., Simo-Serra, E., Ishikawa, H.: Globally and locally consistent image completion. ACM Transactions on Graphics (TOG)
2017
Cited alongside, same era.
Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)
2017
Cited alongside, same era.
Luan, F., Paris, S., Shechtman, E., Bala, K.: Deep photo style transfer. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)
2017
Cited alongside, same era.
Sangkloy, P., Lu, J., Fang, C., Yu, F., Hays, J.: Scribbler: Controlling deep image synthesis with sketch and color. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)
2017
Cited alongside, same era.
Zhou, Y., Zhu, Z., Bai, X., Lischinski, D., Cohen-Or, D., Huang, H.: Non-stationary texture synthesis by adversarial expansion. ACM Transactions on Graphics (TOG)
2018
Later among the works it cites.
Abdal, R., Qin, Y., Wonka, P.: Image2stylegan: How to embed images into the stylegan latent space? In: IEEE International Conference on Computer Vision (ICCV) (2019)
2019
Later among the works it cites.
Bau, D., Strobelt, H., Peebles, W., Wulff, J., Zhou, B., Zhu, J.Y., Torralba, A.: Semantic photo manipulation with a generative image prior. ACM Transactions on Graphics (TOG)
2019
Later among the works it cites.
Bau, D., Zhu, J.Y., Strobelt, H., Bolei, Z., Tenenbaum, J.B., Freeman, W.T., Torralba, A.: Gan dissection: Visualizing and understanding generative adversarial networks. In: International Conference on Learning Representations (ICLR) (2019)
2019
Later among the works it cites.
Brock, A., Donahue, J., Simonyan, K.: Large scale gan training for high fidelity natural image synthesis. In: International Conference on Learning Representations (ICLR) (2019)
2019
Later among the works it cites.
Esser, P., Haux, J., Ommer, B.: Unsupervised robust disentangling of latent characteristics for image synthesis. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 2699–2709 (2019)
2019
Later among the works it cites.
Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
Later among the works it cites.
Kazemi, H., Iranmanesh, S.M., Nasrabadi, N.: Style and content disentanglement in generative adversarial networks. In: 2019 IEEE Winter Conference on Applications of Computer Vision (WACV). pp. 848–856. IEEE (2019)
2019
Later among the works it cites.
Kolkin, N., Salavon, J., Shakhnarovich, G.: Style transfer by relaxed optimal transport and self-similarity. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
Later among the works it cites.
Kotovenko, D., Sanakoyeu, A., Lang, S., Ommer, B.: Content and style disentanglement for artistic style transfer. In: IEEE International Conference on Computer Vision (ICCV) (2019)
2019
Later among the works it cites.
Lin, J., Chen, Z., Xia, Y., Liu, S., Qin, T., Luo, J.: Exploring explicit domain supervision for latent space disentanglement in unpaired image-to-image translation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (2019)
2019
Later among the works it cites.
Liu, M.Y., Huang, X., Mallya, A., Karras, T., Aila, T., Lehtinen, J., Kautz, J.: Few-shot unsupervised image-to-image translation. In: IEEE International Conference on Computer Vision (ICCV) (2019)
2019
Later among the works it cites.
Park, T., Liu, M.Y., Wang, T.C., Zhu, J.Y.: Semantic image synthesis with spatially-adaptive normalization. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
Later among the works it cites.
Shaham, T.R., Dekel, T., Michaeli, T.: Singan: Learning a generative model from a single natural image. In: IEEE International Conference on Computer Vision (ICCV) (2019)
2019
Later among the works it cites.
Shocher, A., Bagon, S., Isola, P., Irani, M.: Ingan: Capturing and remapping the" dna" of a natural image. In: IEEE International Conference on Computer Vision (ICCV) (2019)
2019
Later among the works it cites.
Singh, K.K., Ojha, U., Lee, Y.J.: Finegan: Unsupervised hierarchical disentanglement for fine-grained object generation and discovery. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
Later among the works it cites.
2019
Later among the works it cites.
Xing, X., Han, T., Gao, R., Zhu, S.C., Wu, Y.N.: Unsupervised disentangling of appearance and geometry by deformable generator network. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
Later among the works it cites.
Yoo, J., Uh, Y., Chun, S., Kang, B., Ha, J.W.: Photorealistic style transfer via wavelet transforms. In: IEEE International Conference on Computer Vision (ICCV) (2019)
2019
Later among the works it cites.
Yu, X., Chen, Y., Liu, S., Li, T., Li, G.: Multi-mapping image-to-image translation via learning disentanglement. In: Advances in Neural Information Processing Systems (NeurIPS) (2019)
2019
Later among the works it cites.
Zhang, R.: Making convolutional networks shift-invariant again. In: International Conference on Machine Learning (ICML) (2019)
2019
Later among the works it cites.
Anokhin, I., Solovev, P., Korzhenkov, D., Kharlamov, A., Khakhulin, T., Silvestrov, A., Nikolenko, S., Lempitsky, V., Sterkin, G.: High-resolution daytime translation without domain labels. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2020)
2020
Closest in time.
Choi, Y., Uh, Y., Yoo, J., Ha, J.W.: Stargan v2: Diverse image synthesis for multiple domains. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2020)
2020
Closest in time.
Härkönen, E., Hertzmann, A., Lehtinen, J., Paris, S.: Ganspace: Discovering interpretable gan controls. In: Advances in Neural Information Processing Systems (2020)
2020
Closest in time.
Jahanian, A., Chai, L., Isola, P.: On the”steerability" of generative adversarial networks. In: International Conference on Learning Representations (ICLR) (2020)
2020
Closest in time.
Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., Aila, T.: Analyzing and improving the image quality of stylegan. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
2020
Closest in time.
Pidhorskyi, S., Adjeroh, D.A., Doretto, G.: Adversarial latent autoencoders. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
2020
Closest in time.
Wang, S.Y., Wang, O., Zhang, R., Owens, A., Efros, A.A.: Cnn-generated images are surprisingly easy to spot… for now. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
2020
Closest in time.