Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation
暂无分享,去创建一个
Alexei A. Efros | Eli Shechtman | Philip H.S. Torr | Richard Zhang | Oliver Wang | Puneet K. Dokania | Arnab Ghosh
[1] Léon Bottou,et al. Towards Principled Methods for Training Generative Adversarial Networks , 2017, ICLR.
[2] Ole Winther,et al. Autoencoding beyond pixels using a learned similarity metric , 2015, ICML.
[3] Aaron C. Courville,et al. Adversarially Learned Inference , 2016, ICLR.
[4] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Timo Aila,et al. A Style-Based Generator Architecture for Generative Adversarial Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Alexei A. Efros,et al. Colorful Image Colorization , 2016, ECCV.
[7] Jaakko Lehtinen,et al. Progressive Growing of GANs for Improved Quality, Stability, and Variation , 2017, ICLR.
[8] D. Cohen,et al. Why can't most people draw what they see? , 1997, Journal of experimental psychology. Human perception and performance.
[9] David Pfau,et al. Unrolled Generative Adversarial Networks , 2016, ICLR.
[10] Oriol Vinyals,et al. Synthesizing Programs for Images using Reinforced Adversarial Learning , 2018, ICML.
[11] Paul Smolensky,et al. Information processing in dynamical systems: foundations of harmony theory , 1986 .
[12] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[13] Ian J. Goodfellow,et al. NIPS 2016 Tutorial: Generative Adversarial Networks , 2016, ArXiv.
[14] Ivan E. Sutherland,et al. Sketch pad a man-machine graphical communication system , 1964, DAC.
[15] Taesung Park,et al. Semantic Image Synthesis With Spatially-Adaptive Normalization , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Serge J. Belongie,et al. Convolutional Networks with Adaptive Inference Graphs , 2017, International Journal of Computer Vision.
[17] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[18] Alexei A. Efros,et al. Toward Multimodal Image-to-Image Translation , 2017, NIPS.
[19] Jonathon Shlens,et al. Conditional Image Synthesis with Auxiliary Classifier GANs , 2016, ICML.
[20] Alexei A. Efros,et al. Generative Visual Manipulation on the Natural Image Manifold , 2016, ECCV.
[21] Philip H. S. Torr,et al. Multi-agent Diverse Generative Adversarial Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[22] Yong Jae Lee,et al. ShadowDraw: real-time user guidance for freehand drawing , 2011, ACM Trans. Graph..
[23] Eli Shechtman,et al. Im2Pencil: Controllable Pencil Illustration From Photographs , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[25] Wojciech Zaremba,et al. Improved Techniques for Training GANs , 2016, NIPS.
[26] Alex Graves,et al. Conditional Image Generation with PixelCNN Decoders , 2016, NIPS.
[27] James Hays,et al. SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[28] Kristen Grauman,et al. Fine-Grained Visual Comparisons with Local Learning , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[29] Sebastian Nowozin,et al. Which Training Methods for GANs do actually Converge? , 2018, ICML.
[30] Andrea Vedaldi,et al. Instance Normalization: The Missing Ingredient for Fast Stylization , 2016, ArXiv.
[31] Sepp Hochreiter,et al. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium , 2017, NIPS.
[32] Aaron C. Courville,et al. FiLM: Visual Reasoning with a General Conditioning Layer , 2017, AAAI.
[33] Trevor Darrell,et al. Adversarial Feature Learning , 2016, ICLR.
[34] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[35] Pieter Abbeel,et al. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets , 2016, NIPS.
[36] A. Savitzky,et al. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .
[37] Léon Bottou,et al. Wasserstein GAN , 2017, ArXiv.
[38] Ryan Schmidt,et al. On expert performance in 3D curve-drawing tasks , 2009, SBIM '09.
[39] Rob Fergus,et al. Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks , 2015, NIPS.
[40] K. Sasaki,et al. Learning to simplify , 2016, ACM Trans. Graph..
[41] Yuichi Yoshida,et al. Spectral Normalization for Generative Adversarial Networks , 2018, ICLR.
[42] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[43] Alexei A. Efros,et al. Context Encoders: Feature Learning by Inpainting , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[44] Chuang Gan,et al. Sparse, Smart Contours to Represent and Edit Images , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[45] Douglas Eck,et al. A Neural Representation of Sketch Drawings , 2017, ICLR.
[46] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[47] Serge J. Belongie,et al. Residual Networks Behave Like Ensembles of Relatively Shallow Networks , 2016, NIPS.
[48] Marc Alexa,et al. Photosketcher: Interactive Sketch-Based Image Synthesis , 2011, IEEE Computer Graphics and Applications.
[49] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[50] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[51] Matthias Zwicker,et al. Faceshop , 2018, ACM Trans. Graph..
[52] Jan Kautz,et al. Multimodal Unsupervised Image-to-Image Translation , 2018, ECCV.
[53] Fisher Yu,et al. Scribbler: Controlling Deep Image Synthesis with Sketch and Color , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[54] Han Zhang,et al. Self-Attention Generative Adversarial Networks , 2018, ICML.
[55] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[56] Jan Kautz,et al. High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[57] Serge J. Belongie,et al. Arbitrary Style Transfer in Real-Time with Adaptive Instance Normalization , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[58] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[59] Sung Yong Shin,et al. On pixel-based texture synthesis by non-parametric sampling , 2006, Comput. Graph..
[60] Adam Finkelstein,et al. Where do people draw lines? , 2008, ACM Trans. Graph..
[61] Yann LeCun,et al. Deep multi-scale video prediction beyond mean square error , 2015, ICLR.
[62] Alexei A. Efros,et al. Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[63] 拓海 杉山,et al. “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .
[64] Yoshua Bengio,et al. Mode Regularized Generative Adversarial Networks , 2016, ICLR.