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Generative models have made immense progress in recent years, particularly in their ability to generate high quality images.
Reporting bias and knowledge extraction
Gordon, Jonathan and Van Durme, Benjamin · 2013
Earlier work this paper cites.
Convolutional neural networks for no-reference image quality assessment
Kang, Le, Ye, Peng, Li, Yi, and Doermann, David · 2014
Earlier work this paper cites.
Deep generative image models using a laplacian pyramid of adversarial networks
Denton, Emily L, Chintala, Soumith, Fergus, Rob, et al · 2015
Earlier work this paper cites.
A note on the evaluation of generative models
Theis, Lucas, Oord, Aäron van den, and Bethge, Matthias · 2015
Earlier work this paper cites.
Seeing through the human reporting bias: Visual classifiers from noisy human-centric labels
Misra, Ishan, Lawrence Zitnick, C, Mitchell, Margaret, and Girshick, Ross · 2016
Earlier work this paper cites.
Improved techniques for training gans
Salimans, Tim, Goodfellow, Ian, Zaremba, Wojciech, Cheung, Vicki, Radford, Alec, and Chen, Xi · 2016
Earlier work this paper cites.
Colorful image colorization
Zhang, Richard, Isola, Phillip, and Efros, Alexei A · 2016
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, Martin, Ramsauer, Hubert, Unterthiner, Thomas, Nessler, Bernhard, and Hochreiter, Sepp · 2017
Earlier work this paper cites.
Stacked generative adversarial networks
Huang, Xun, Li, Yixuan, Poursaeed, Omid, Hopcroft, John, and Belongie, Serge · 2017
Earlier work this paper cites.
Image-to-image translation with conditional adversarial networks
Isola, Phillip, Zhu, Jun-Yan, Zhou, Tinghui, and Efros, Alexei A · 2017
Cited alongside, same era.
Progressive growing of gans for improved quality, stability, and variation
Karras, Tero, Aila, Timo, Laine, Samuli, and Lehtinen, Jaakko · 2017
Cited alongside, same era.
Towards an automatic turing test: Learning to evaluate dialogue responses
Lowe, Ryan, Noseworthy, Michael, Serban, Iulian V, Angelard-Gontier, Nicolas, Bengio, Yoshua, and Pineau, Joelle · 2017
Cited alongside, same era.
Medical image synthesis with context-aware generative adversarial networks
Nie, Dong, Trullo, Roger, Lian, Jun, Petitjean, Caroline, Ruan, Su, Wang, Qian, and Shen, Dinggang · 2017
Cited alongside, same era.
Learning to generate images with perceptual similarity metrics
Snell, Jake, Ridgeway, Karl, Liao, Renjie, Roads, Brett D, Mozer, Michael C, and Zemel, Richard S · 2017
Fashion-gen: The generative fashion dataset and challenge
Rostamzadeh, Negar, Hosseini, Seyedarian, Boquet, Thomas, Stokowiec, Wojciech, Zhang, Ying, Jauvin, Christian, and Pal, Chris · 2018
Later among the works it cites.
Generating adversarial examples with adversarial networks
Xiao, Chaowei, Li, Bo, Zhu, Jun-Yan, He, Warren, Liu, Mingyan, and Song, Dawn · 2018
Later among the works it cites.
The unreasonable effectiveness of deep features as a perceptual metric
Zhang, Richard, Isola, Phillip, Efros, Alexei A, Shechtman, Eli, and Wang, Oliver · 2018
Later among the works it cites.
Pros and cons of gan evaluation measures
Borji, Ali · 2019
Closest in time.
Gansynth: Adversarial neural audio synthesis
Engel, Jesse, Agrawal, Kumar Krishna, Chen, Shuo, Gulrajani, Ishaan, Donahue, Chris, and Roberts, Adam · 2019
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Cited alongside, same era.
Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Zhang, Han, Xu, Tao, Li, Hongsheng, Zhang, Shaoting, Wang, Xiaogang, Huang, Xiaolei, and Metaxas, Dimitris N · 2017
Cited alongside, same era.
Barratt, Shane and Sharma, Rishi · 2018
Cited alongside, same era.
Large scale gan training for high fidelity natural image synthesis
Brock, Andrew, Donahue, Jeff, and Simonyan, Karen · 2018
Cited alongside, same era.
Pieapp: Perceptual image-error assessment through pairwise preference
Prashnani, Ekta, Cai, Hong, Mostofi, Yasamin, and Sen, Pradeep · 2018
Cited alongside, same era.
Closest in time.
Unifying human and statistical evaluation for natural language generation
Hashimoto, Tatsunori B, Zhang, Hugh, and Liang, Percy · 2019
Closest in time.
Improved precision and recall metric for assessing generative models
Kynkäänniemi, Tuomas, Karras, Tero, Laine, Samuli, Lehtinen, Jaakko, and Aila, Timo · 2019
Closest in time.
Hype: Human eye perceptual evaluation of generative models
Zhou, Sharon, Gordon, Mitchell, Krishna, Ranjay, Narcomey, Austin, Morina, Durim, and Bernstein, Michael S · 2019
Closest in time.