arXiv Open Access 2022

Neural Neighbor Style Transfer

Nicholas Kolkin Michal Kucera Sylvain Paris Daniel Sykora Eli Shechtman +1 lainnya

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Abstrak

We propose Neural Neighbor Style Transfer (NNST), a pipeline that offers state-of-the-art quality, generalization, and competitive efficiency for artistic style transfer. Our approach is based on explicitly replacing neural features extracted from the content input (to be stylized) with those from a style exemplar, then synthesizing the final output based on these rearranged features. While the spirit of our approach is similar to prior work, we show that our design decisions dramatically improve the final visual quality.

Topik & Kata Kunci

cs.CV cs.GR

Penulis (6)

Nicholas Kolkin

Michal Kucera

Sylvain Paris

Daniel Sykora

Eli Shechtman

Greg Shakhnarovich

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APA MLA BibTeX

Kolkin, N., Kucera, M., Paris, S., Sykora, D., Shechtman, E., Shakhnarovich, G. (2022). Neural Neighbor Style Transfer. https://arxiv.org/abs/2203.13215

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓