Fetching the paper…
Reading the bibliography…
We propose a novel method for solving regression tasks using few-shot or weak supervision.
ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
Scikit-learn: Machine learning in python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al · 2011
Earlier work this paper cites.
3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
Earlier work this paper cites.
Cross-age reference coding for age-invariant face recognition and retrieval
Bor-Chun Chen, Chu-Song Chen, and Winston H. Hsu · 2014
Earlier work this paper cites.
Generative adversarial networks
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
David Hughes, Marcel Salathé, et al · 2015
Earlier work this paper cites.
Dex: Deep expectation of apparent age from a single image
Rasmus Rothe, Radu Timofte, and Luc Van Gool · 2015
Earlier work this paper cites.
Unsupervised and semi-supervised learning with categorical generative adversarial networks
Jost Tobias Springenberg · 2015
Earlier work this paper cites.
A large-scale car dataset for fine-grained categorization and verification
Linjie Yang, Ping Luo, Chen Change Loy, and Xiaoou Tang · 2015
Earlier work this paper cites.
Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, and Jianxiong Xiao · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Semi-supervised learning with generative adversarial networks
Augustus Odena · 2016
Earlier work this paper cites.
Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
Earlier work this paper cites.
Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, and Daan Wierstra · 2016
Earlier work this paper cites.
Data augmentation generative adversarial networks
Antreas Antoniou, Amos Storkey, and Harrison Edwards · 2017
Earlier work this paper cites.
Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
Earlier work this paper cites.
Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
Earlier work this paper cites.
Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, et al · 2017
Earlier work this paper cites.
The effectiveness of data augmentation in image classification using deep learning
Luis Perez and Jason Wang · 2017
Earlier work this paper cites.
Learning to compose domain-specific transformations for data augmentation
Alexander J Ratner, Henry R Ehrenberg, Zeshan Hussain, Jared Dunnmon, and Christopher Ré · 2017
Earlier work this paper cites.
Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard S Zemel · 2017
Earlier work this paper cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
Earlier work this paper cites.
Data augmentation in emotion classification using generative adversarial networks
Xinyue Zhu, Yifan Liu, Zengchang Qin, and Jiahong Li · 2017
Earlier work this paper cites.
Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
Earlier work this paper cites.
Gan-based synthetic medical image augmentation for increased cnn performance in liver lesion classification
Maayan Frid-Adar, Idit Diamant, Eyal Klang, Michal Amitai, Jacob Goldberger, and Hayit Greenspan · 2018
Earlier work this paper cites.
Few-shot human motion prediction via meta-learning
Liang-Yan Gui, Yu-Xiong Wang, Deva Ramanan, and José MF Moura · 2018
Earlier work this paper cites.
Bagan: Data augmentation with balancing gan
Giovanni Mariani, Florian Scheidegger, Roxana Istrate, Costas Bekas, and Cristiano Malossi · 2018
Earlier work this paper cites.
Few-shot segmentation propagation with guided networks
Kate Rakelly, Evan Shelhamer, Trevor Darrell, Alexei A Efros, and Sergey Levine · 2018
Cited alongside, same era.
How good is my gan?
Konstantin Shmelkov, Cordelia Schmid, and Karteek Alahari · 2018
Cited alongside, same era.
Rendergan: Generating realistic labeled data
Leon Sixt, Benjamin Wild, and Tim Landgraf · 2018
Cited alongside, same era.
Learning to compare: Relation network for few-shot learning
Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip HS Torr, and Timothy M Hospedales · 2018
Cited alongside, same era.
Low-shot learning from imaginary data
Yu-Xiong Wang, Ross Girshick, Martial Hebert, and Bharath Hariharan · 2018
Cited alongside, same era.
Image2stylegan: How to embed images into the stylegan latent space?
Rameen Abdal, Yipeng Qin, and Peter Wonka · 2019
Face identity disentanglement via latent space mapping
Yotam Nitzan, A. Bermano, Yangyan Li, and D. Cohen-Or · 2020
Later among the works it cites.
Fair attribute classification through latent space de-biasing
Vikram V Ramaswamy, Sunnis SY Kim, and Olga Russakovsky · 2020
Later among the works it cites.
Encoding in style: a stylegan encoder for image-to-image translation
Elad Richardson, Yuval Alaluf, Or Patashnik, Yotam Nitzan, Yaniv Azar, Stav Shapiro, and Daniel Cohen-Or · 2020
Later among the works it cites.
Stylegan2-pytorch
Kim Seonghyeon · 2020
Later among the works it cites.
Contrastive examples for addressing the tyranny of the majority
Viktoriia Sharmanska, Lisa Anne Hendricks, Trevor Darrell, and Novi Quadrianto · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Fair generative modeling via weak supervision
Aditya Grover, Kristy Choi, Rui Shu, and Stefano Ermon · 2019
Cited alongside, same era.
On the”steerability” of generative adversarial networks
Ali Jahanian, Lucy Chai, and Phillip Isola · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
Cited alongside, same era.
Few-shot unsupervised image-to-image translation
Ming-Yu Liu, Xun Huang, Arun Mallya, Tero Karras, Timo Aila, Jaakko Lehtinen, and Jan Kautz · 2019
Cited alongside, same era.
Few-shot adaptive gaze estimation
Seonwook Park, Shalini De Mello, Pavlo Molchanov, Umar Iqbal, Otmar Hilliges, and Jan Kautz · 2019
Cited alongside, same era.
Classification accuracy score for conditional generative models
Suman Ravuri and Oriol Vinyals · 2019
Cited alongside, same era.
Interpreting the latent space of gans for semantic face editing
Yujun Shen, Jinjin Gu, Xiaoou Tang, and Bolei Zhou · 2020
Later among the works it cites.
Closed-form factorization of latent semantics in gans
Yujun Shen and Bolei Zhou · 2020
Later among the works it cites.
Meta-transfer learning for zero-shot super-resolution
Jae Woong Soh, Sunwoo Cho, and Nam Ik Cho · 2020
Later among the works it cites.
Gan steerability without optimization
Nurit Spingarn-Eliezer, Ron Banner, and Tomer Michaeli · 2020
Later among the works it cites.
Generalizing from a few examples: A survey on few-shot learning
Yaqing Wang, Quanming Yao, James T Kwok, and Lionel M Ni · 2020
Later among the works it cites.
Multi-scale positive sample refinement for few-shot object detection
Jiaxi Wu, Songtao Liu, Di Huang, and Yunhong Wang · 2020
Later among the works it cites.
Stylespace analysis: Disentangled controls for stylegan image generation, 2020
Zongze Wu, Dani Lischinski, and Eli Shechtman · 2020
Later among the works it cites.
Few-shot object detection and viewpoint estimation for objects in the wild
Yang Xiao and Renaud Marlet · 2020
Later among the works it cites.
Generative hierarchical features from synthesizing images
Yinghao Xu, Yujun Shen, Jiapeng Zhu, Ceyuan Yang, and Bolei Zhou · 2020
Later among the works it cites.
Whenet: Real-time fine-grained estimation for wide range head pose
Yijun Zhou and James Gregson · 2020
Later among the works it cites.
In-domain gan inversion for real image editing
Jiapeng Zhu, Yujun Shen, Deli Zhao, and Bolei Zhou · 2020
Later among the works it cites.
Restyle: A residual-based stylegan encoder via iterative refinement
Yuval Alaluf, Or Patashnik, and Daniel Cohen-Or · 2021
Closest in time.
Ensembling with deep generative views
Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, and Richard Zhang · 2021
Closest in time.
Few-shot semantic image synthesis using stylegan prior
Yuki Endo and Yoshihiro Kanamori · 2021
Closest in time.
Style encoding for class-specific image generation
Dana Cohen Hochberg, Raja Giryes, and Hayit Greenspan · 2021
Closest in time.
Explaining in style: Training a gan to explain a classifier in stylespace
Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T Freeman, Phillip Isola, Amir Globerson, Michal Irani, et al · 2021
Closest in time.
Styleclip: Text-driven manipulation of stylegan imagery
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski · 2021
Closest in time.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Closest in time.
Designing an encoder for stylegan image manipulation
Omer Tov, Yuval Alaluf, Yotam Nitzan, Or Patashnik, and Daniel Cohen-Or · 2021
Closest in time.
Weihao Xia, Yulun Zhang, Yujiu Yang, Jing-Hao Xue, Bolei Zhou, and Ming-Hsuan Yang · 2021
Closest in time.
Posecontrast: Class-agnostic object viewpoint estimation in the wild with pose-aware contrastive learning
Yang Xiao, Yuming Du, and Renaud Marlet · 2021
Closest in time.