Fetching the paper…
Reading the bibliography…
It is common but challenging to address high-resolution image blending in the automatic photo editing application.
The Laplacian pyramid as a compact image code
Peter Burt and Edward Adelson. 1983 · 1983
Earlier work this paper cites.
A method for enforcing integrability in shape from shading algorithms
Robert T. Frankot and Rama Chellappa. 1988 · 1988
Earlier work this paper cites.
Eliminating ghosting and exposure artifacts in image mosaics. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 2
Matthew Uyttendaele, Ashley Eden, and Richard Szeliski. 2001 · 2001
Earlier work this paper cites.
Gradient domain high dynamic range compression
Raanan Fattal, Dani Lischinski, and Michael Werman. 2002 · 2002
Earlier work this paper cites.
Poisson image editing
Patrick Pérez, Michel Gangnet, and Andrew Blake. 2003 · 2003
Earlier work this paper cites.
Interactive digital photomontage
A. Agarwala, M. Dontcheva, M. Agrawala, S. Drucker, A. Colburn, B. Curless, D. Salesin, and M. Cohen. 2004 · 2004
Earlier work this paper cites.
Seamless image stitching in the gradient domain. In The European Conference on Computer Vision (ECCV) . 377–389
A. Levin, A. Zomet, S. Peleg, and Y. Weiss. 2004 · 2004
Earlier work this paper cites.
Drag-and-drop pasting
J. Jia, J. Sun, C.K. Tang, and H.Y. Shum. 2006 · 2006
Earlier work this paper cites.
Streaming multigrid for gradient-domain operations on large images
M. Kazhdan and H. Hoppe. 2008 · 2008
Earlier work this paper cites.
LabelMe: a database and web-based tool for image annotation
Bryan C Russell, Antonio Torralba, Kevin P Murphy, and William T Freeman. 2008 · 2008
Earlier work this paper cites.
Fast image blending using watersheds and graph cuts
Nuno Gracias, Mohammad Mahoor, Shahriar Negahdaripour, and Arthur Gleason. 2009 · 2009
Earlier work this paper cites.
Seamless image cloning by a closed form solution of a modified poisson problem. In SIGGRAPH Asia . 15
Masayuki Tanaka, Ryo Kamio, and Masatoshi Okutomi. 2012 · 2012
Earlier work this paper cites.
Understanding and improving the realism of image composites
Su Xue, Aseem Agarwala, Julie Dorsey, and Holly Rushmeier. 2012 · 2012
Earlier work this paper cites.
Generative adversarial nets. In Advances in Neural Information Processing Systems (NIPS) . 2672–2680
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Cited alongside, same era.
Transient Attributes for High-Level Understanding and Editing of Outdoor Scenes
Pierre-Yves Laffont, Zhile Ren, Xiaofeng Tao, Chao Qian, and James Hays. 2014 · 2014
Cited alongside, same era.
Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero. 2014 · 2014
Cited alongside, same era.
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks. In Advances in Neural Information Processing Systems (NIPS) . 1486–1494
Emily Denton, Soumith Chintala, Arthur Szlam, and Rob Fergus. 2015 · 2015
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks. In The European Conference on Computer Vision (ECCV) . 702–716
Chuang Li and Michael Wand. 2016 · 2016
Later among the works it cites.
Context encoders: Feature learning by inpainting. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 2536–2544
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros. 2016 · 2016
Later among the works it cites.
Generative Adversarial Text to Image Synthesis. In International Conference on Machine Learning (ICML) . 1060–1069
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee. 2016 · 2016
Later among the works it cites.
Improved techniques for training GANs. In Advances in Neural Information Processing Systems (NIPS) . 2234–2242
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi. Chen. 2016 · 2016
Later among the works it cites.
Generative image modeling using style and structure adversarial networks. In The European Conference on Computer Vision (ECCV) . 318–335
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
DRAW: A recurrent neural network for image generation. In International Conference on Machine Learning (ICML) . 1462–1471
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, and Daan Wierstra. 2015 · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy. 2015 · 2015
Cited alongside, same era.
Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala. 2015 · 2015
Cited alongside, same era.
Chainer: a next-generation open source framework for deep learning. In Proceedings of Workshop on Machine Learning Systems in NIPS . 1–6
Seiya Tokui, Kenta Oono, Shohei Hido, and Justin Clayton. 2015 · 2015
Cited alongside, same era.
Learning a discriminative model for the perception of realism in composite images. In The IEEE International Conference on Computer Vision (ICCV) . 3943–3951
Jun-Yan Zhu, Philipp Krahenbuhl, Eli Shechtman, and Alexei A Efros. 2015 · 2015
Cited alongside, same era.
Infogan: Interpretable representation learning by information maximizing generative adversarial nets. In Advances in Neural Information Processing Systems (NIPS) . 2172–2180
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel. 2016 · 2016
Cited alongside, same era.
Generating images with perceptual similarity metrics based on deep networks. In Advances in Neural Information Processing Systems (NIPS) . 658–666
Alexey Dosovitskiy and Thomas Brox. 2016 · 2016
Cited alongside, same era.
Xiaolong Wang and Abhinav Gupta. 2016 · 2016
Later among the works it cites.
Pixellevel domain transfer. In The European Conference on Computer Vision (ECCV) . 517–532
Donggeun Yoo, Namil Kim, Sunggyun Park, Anthony S. Paek, and In So Kweon. 2016 · 2016
Later among the works it cites.
Generative visual manipulation on the natural image manifold. In The European Conference on Computer Vision (ECCV) . 597–613
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, and Alexei A Efros. 2016 · 2016
Later among the works it cites.
Wasserstein Generative Adversarial Networks. In International Conference on Machine Learning (ICML) . 214–223
Martin Arjovsky, Soumith Chintala, and Léon Bottou. 2017 · 2017
Closest in time.
Image-to-Image Translation with Conditional Adversarial Networks. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 5967–5976
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros. 2017 · 2017
Closest in time.
Deep image harmonization. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Yi-Hsuan Tsai, Xiaohui Shen, Zhe Lin, Kalyan Sunkavalli, Xin Lu, and Ming-Hsuan Yang. 2017 · 2017
Closest in time.
Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaolei Huang, Xiaogang Wang, and Dimitris Metaxas. 2017 · 2017
Closest in time.
Loss Functions for Image Restoration With Neural Networks
H. Zhao, O. Gallo, I. Frosio, and J. Kautz. 2017 · 2017
Closest in time.