Stylespace analysis: Disentangled controls for stylegan image generation
Z Wu, D Lischinski… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
We explore and analyze the latent style space of StyleGAN2, a state-of-the-art architecture
for image generation, using models pretrained on several different datasets. We first show …
for image generation, using models pretrained on several different datasets. We first show …
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
Z Wu, D Lischinski, E Shechtman - 2021 IEEE/CVF Conference …, 2021 - ieeexplore.ieee.org
We explore and analyze the latent style space of Style-GAN2, a state-of-the-art architecture
for image generation, using models pretrained on several different datasets. We first show …
for image generation, using models pretrained on several different datasets. We first show …
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
Z Wu, D Lischinski, E Shechtman - arXiv preprint arXiv:2011.12799, 2020 - arxiv.org
We explore and analyze the latent style space of StyleGAN2, a state-of-the-art architecture
for image generation, using models pretrained on several different datasets. We first show …
for image generation, using models pretrained on several different datasets. We first show …
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
Z Wu, D Lischinski, E Shechtman - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
We explore and analyze the latent style space of StyleGAN2, a state-of-the-art architecture
for image generation, using models pretrained on several different datasets. We first show …
for image generation, using models pretrained on several different datasets. We first show …
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
Z Wu, D Lischinski… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
We explore and analyze the latent style space of StyleGAN2, a state-of-the-art architecture
for image generation, using models pretrained on several different datasets. We first show …
for image generation, using models pretrained on several different datasets. We first show …
[引用][C] StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
Z Wu, D Lischinski, E Shechtman - 2021 IEEE/CVF Conference on …, 2021 - cir.nii.ac.jp
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation | CiNii Research
CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ移動 論文・データを …
CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ移動 論文・データを …
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
Z Wu, D Lischinski, E Shechtman - 2021 IEEE/CVF Conference on …, 2021 - computer.org
We explore and analyze the latent style space of Style-GAN2, a state-of-the-art architecture
for image generation, using models pretrained on several different datasets. We first show …
for image generation, using models pretrained on several different datasets. We first show …