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Neural style transfer: A review
The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks
(CNNs) in creating artistic imagery by separating and recombining image content and style …
(CNNs) in creating artistic imagery by separating and recombining image content and style …
CNN architectures for geometric transformation-invariant feature representation in computer vision: a review
A Mumuni, F Mumuni - SN Computer Science, 2021 - Springer
One of the main challenges in machine vision relates to the problem of obtaining robust
representation of visual features that remain unaffected by geometric transformations. This …
representation of visual features that remain unaffected by geometric transformations. This …
Dataset distillation via factorization
In this paper, we study dataset distillation (DD), from a novel perspective and introduce
a\emph {dataset factorization} approach, termed\emph {HaBa}, which is a plug-and-play …
a\emph {dataset factorization} approach, termed\emph {HaBa}, which is a plug-and-play …
Adaattn: Revisit attention mechanism in arbitrary neural style transfer
Fast arbitrary neural style transfer has attracted widespread attention from academic,
industrial and art communities due to its flexibility in enabling various applications. Existing …
industrial and art communities due to its flexibility in enabling various applications. Existing …
General image-to-image translation with one-shot image guidance
Large-scale text-to-image models pre-trained on massive text-image pairs show excellent
performance in image synthesis recently. However, image can provide more intuitive visual …
performance in image synthesis recently. However, image can provide more intuitive visual …
Lightweight image super-resolution with expectation-maximization attention mechanism
X Zhu, K Guo, S Ren, B Hu, M Hu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In recent years, with the rapid development of deep learning, super-resolution methods
based on convolutional neural networks (CNNs) have made great progress. However, the …
based on convolutional neural networks (CNNs) have made great progress. However, the …
Aespa-net: Aesthetic pattern-aware style transfer networks
To deliver the artistic expression of the target style, recent studies exploit the attention
mechanism owing to its ability to map the local patches of the style image to the …
mechanism owing to its ability to map the local patches of the style image to the …
Styleformer: Real-time arbitrary style transfer via parametric style composition
In this work, we propose a new feed-forward arbitrary style transfer method, referred to as
StyleFormer, which can simultaneously fulfill fine-grained style diversity and semantic …
StyleFormer, which can simultaneously fulfill fine-grained style diversity and semantic …
Amalgamating knowledge from heterogeneous graph neural networks
In this paper, we study a novel knowledge transfer task in the domain of graph neural
networks (GNNs). We strive to train a multi-talented student GNN, without accessing human …
networks (GNNs). We strive to train a multi-talented student GNN, without accessing human …
A style-aware content loss for real-time hd style transfer
A Sanakoyeu, D Kotovenko, S Lang… - proceedings of the …, 2018 - openaccess.thecvf.com
Recently style transfer has received a lot of attention. While much of this research has aimed
at speeding up the processing, the approaches are still lacking from a principled, art …
at speeding up the processing, the approaches are still lacking from a principled, art …