Built on

S. Guan, Y. Tai, B. Ni, F. Zhu, F. Huang, X. Yang, Collaborative learning for faster stylegan embedding, arXiv preprint arXiv:2007.01758
Original
2007
Earlier work this paper cites.
Y. Shen, B. Zhou, Closed-form factorization of latent semantics in gans, arXiv preprint arXiv:2007.06600
Original
2007
Earlier work this paper cites.
R. Abdal, P. Zhu, N. Mitra, P. Wonka, Styleflow: Attribute-conditioned exploration of stylegan-generated images using conditional continuous normalizing flows, arXiv e-prints (2020) arXiv–2008
2008
Earlier work this paper cites.
E. Richardson, Y. Alaluf, O. Patashnik, Y. Nitzan, Y. Azar, S. Shapiro, D. Cohen-Or, Encoding in style: a stylegan encoder for image-to-image translation, arXiv preprint arXiv:2008.00951
Original
2008
Earlier work this paper cites.
Y. Liu, Q. Li, Z. Sun, T. Tan, Style intervention: How to achieve spatial disentanglement with style-based generators?, arXiv preprint arXiv:2011.09699
Original
2011
Earlier work this paper cites.
Z. Wu, D. Lischinski, E. Shechtman, Stylespace analysis: Disentangled controls for stylegan image generation, arXiv preprint arXiv:2011.12799
Original
2011
Earlier work this paper cites.
X. Hou, X. Zhang, L. Shen, Z. Lai, J. Wan, Guidedstyle: Attribute knowledge guided style manipulation for semantic face editing, arXiv preprint arXiv:2012.11856
Original
2012
Earlier work this paper cites.
P. Zhu, R. Abdal, Y. Qin, P. Wonka, Improved stylegan embedding: Where are the good latents?, arXiv preprint arXiv:2012.09036
Original
2012
Earlier work this paper cites.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio, Generative adversarial nets, in: Z. Ghahramani, M. Welling, C. Cortes, N. Lawrence, K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems, Vol. 27, Curran Associates, Inc., 2014
2014
Earlier work this paper cites.

Similar

R. Rothe, R. Timofte, L. V. Gool, Dex: Deep expectation of apparent age from a single image, in: IEEE International Conference on Computer Vision Workshops (ICCVW), 2015
2015
Cited alongside, same era.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. u. Kaiser, I. Polosukhin, Attention is all you need, in: I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, R. Garnett (Eds.), Advances in Neural Information Processing Systems, Vol. 30, Curran Associates, Inc., 2017
2017
Cited alongside, same era.
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, S. Hochreiter, Gans trained by a two time-scale update rule converge to a local nash equilibrium, in: I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, R. Garnett (Eds.), Advances in Neural Information Processing Systems, Vol. 30, Curran Associates, Inc., 2017
2017
Cited alongside, same era.

Then

E. Härkönen, A. Hertzmann, J. Lehtinen, S. Paris, Ganspace: Discovering interpretable gan controls, in: H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, H. Lin (Eds.), Advances in Neural Information Processing Systems, Vol. 33, Curran Associates, Inc., 2020, pp. 9841–9850
2020
Later among the works it cites.
E. Collins, R. Bala, B. Price, S. Susstrunk, Editing in style: Uncovering the local semantics of gans, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 5771–5780
2020
Later among the works it cites.
R. Abdal, Y. Qin, P. Wonka, Image2stylegan++: How to edit the embedded images?, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 8296–8305
2020
Later among the works it cites.
J. Zhu, Y. Shen, D. Zhao, B. Zhou, In-domain gan inversion for real image editing, in: European Conference on Computer Vision, Springer, 2020, pp. 592–608
2020
Later among the works it cites.

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Reading the bibliography…

2021

Transforming the Latent Space of StyleGAN for Real Face Editing

Li, Heyi, Liu, Jinlong, Zhang, Xinyu et al.

Understand

Despite recent advances in semantic manipulation using StyleGAN, semantic editing of real faces remains challenging.

The gap between the $W$ space and the $W$+ space demands an undesirable trade-off between reconstruction quality and editing quality.
To solve this problem, we propose to expand the latent space by replacing fully-connected layers in the StyleGAN's mapping network with attention-based transformers.
This simple and effective technique integrates the aforementioned two spaces and transforms them into one new latent space called $W$++.

Built on

S. Guan, Y. Tai, B. Ni, F. Zhu, F. Huang, X. Yang, Collaborative learning for faster stylegan embedding, arXiv preprint arXiv:2007.01758
Original
2007
Earlier work this paper cites.
Y. Shen, B. Zhou, Closed-form factorization of latent semantics in gans, arXiv preprint arXiv:2007.06600
Original
2007
Earlier work this paper cites.
R. Abdal, P. Zhu, N. Mitra, P. Wonka, Styleflow: Attribute-conditioned exploration of stylegan-generated images using conditional continuous normalizing flows, arXiv e-prints (2020) arXiv–2008
2008
Earlier work this paper cites.
E. Richardson, Y. Alaluf, O. Patashnik, Y. Nitzan, Y. Azar, S. Shapiro, D. Cohen-Or, Encoding in style: a stylegan encoder for image-to-image translation, arXiv preprint arXiv:2008.00951
Original
2008
Earlier work this paper cites.
Y. Liu, Q. Li, Z. Sun, T. Tan, Style intervention: How to achieve spatial disentanglement with style-based generators?, arXiv preprint arXiv:2011.09699
Original
2011
Earlier work this paper cites.
Z. Wu, D. Lischinski, E. Shechtman, Stylespace analysis: Disentangled controls for stylegan image generation, arXiv preprint arXiv:2011.12799
Original
2011
Earlier work this paper cites.
X. Hou, X. Zhang, L. Shen, Z. Lai, J. Wan, Guidedstyle: Attribute knowledge guided style manipulation for semantic face editing, arXiv preprint arXiv:2012.11856
Original
2012
Earlier work this paper cites.
P. Zhu, R. Abdal, Y. Qin, P. Wonka, Improved stylegan embedding: Where are the good latents?, arXiv preprint arXiv:2012.09036
Original
2012
Earlier work this paper cites.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio, Generative adversarial nets, in: Z. Ghahramani, M. Welling, C. Cortes, N. Lawrence, K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems, Vol. 27, Curran Associates, Inc., 2014
2014
Earlier work this paper cites.

Similar

R. Rothe, R. Timofte, L. V. Gool, Dex: Deep expectation of apparent age from a single image, in: IEEE International Conference on Computer Vision Workshops (ICCVW), 2015
2015
Cited alongside, same era.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. u. Kaiser, I. Polosukhin, Attention is all you need, in: I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, R. Garnett (Eds.), Advances in Neural Information Processing Systems, Vol. 30, Curran Associates, Inc., 2017
2017
Cited alongside, same era.
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, S. Hochreiter, Gans trained by a two time-scale update rule converge to a local nash equilibrium, in: I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, R. Garnett (Eds.), Advances in Neural Information Processing Systems, Vol. 30, Curran Associates, Inc., 2017
2017
Cited alongside, same era.

Then

E. Härkönen, A. Hertzmann, J. Lehtinen, S. Paris, Ganspace: Discovering interpretable gan controls, in: H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, H. Lin (Eds.), Advances in Neural Information Processing Systems, Vol. 33, Curran Associates, Inc., 2020, pp. 9841–9850
2020
Later among the works it cites.
E. Collins, R. Bala, B. Price, S. Susstrunk, Editing in style: Uncovering the local semantics of gans, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 5771–5780
2020
Later among the works it cites.
R. Abdal, Y. Qin, P. Wonka, Image2stylegan++: How to edit the embedded images?, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 8296–8305
2020
Later among the works it cites.
J. Zhu, Y. Shen, D. Zhao, B. Zhou, In-domain gan inversion for real image editing, in: European Conference on Computer Vision, Springer, 2020, pp. 592–608
2020
Later among the works it cites.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

R. Zhang, P. Isola, A. A. Efros, E. Shechtman, O. Wang, The unreasonable effectiveness of deep features as a perceptual metric, in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2018, pp. 586–595

2018

Cited alongside, same era.

T. Karras, S. Laine, T. Aila, A style-based generator architecture for generative adversarial networks, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 4401–4410

2019

Cited alongside, same era.

R. Abdal, Y. Qin, P. Wonka, Image2stylegan: How to embed images into the stylegan latent space?, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019, pp. 4432–4441

2019

Cited alongside, same era.

T. Kynkäänniemi, T. Karras, S. Laine, J. Lehtinen, T. Aila, Improved precision and recall metric for assessing generative models, in: H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, R. Garnett (Eds.), Advances in Neural Information Processing Systems, Vol. 32, Curran Associates, Inc., 2019

2019

Cited alongside, same era.

T. Karras, S. Laine, M. Aittala, J. Hellsten, J. Lehtinen, T. Aila, Analyzing and improving the image quality of stylegan, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 8110–8119

2020

Cited alongside, same era.

Y. Shen, J. Gu, X. Tang, B. Zhou, Interpreting the latent space of gans for semantic face editing, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 9243–9252

2020

Cited alongside, same era.

Y. Shen, C. Yang, X. Tang, B. Zhou, Interfacegan: Interpreting the disentangled face representation learned by gans, IEEE Transactions on Pattern Analysis and Machine Intelligence

Cited in the paper.

A. Shoshan, N. Bhonker, I. Kviatkovsky, G. Medioni, Gan-control: Explicitly controllable gans, arXiv preprint arXiv:2101.02477

Original

Cited in the paper.

M. Mirza, S. Osindero, Conditional generative adversarial nets, arXiv preprint arXiv:1411.1784

Original

Cited in the paper.

A. Tewari, M. Elgharib, F. Bernard, H.-P. Seidel, P. Pérez, M. Zollhöfer, C. Theobalt, Pie: Portrait image embedding for semantic control, ACM Transactions on Graphics (TOG) 39 (6) (2020) 1–14

2020

Later among the works it cites.

A. Tewari, M. Elgharib, G. Bharaj, F. Bernard, H.-P. Seidel, P. Pérez, M. Zollhofer, C. Theobalt, Stylerig: Rigging stylegan for 3d control over portrait images, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 6142–6151

2020

Later among the works it cites.

M. F. Naeem, S. J. Oh, Y. Uh, Y. Choi, J. Yoo, Reliable fidelity and diversity metrics for generative models, in: International Conference on Machine Learning, PMLR, 2020, pp. 7176–7185

2020

Later among the works it cites.

A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, J. Uszkoreit, N. Houlsby, An image is worth 16x16 words: Transformers for image recognition at scale, in: International Conference on Learning Representations, 2021

2021

Closest in time.