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https://github.com/neuralchen/awesome_style_transfer

The style transfer paper collection in International CV conference
https://github.com/neuralchen/awesome_style_transfer
List: awesome_style_transfer
awesome awesome-list deep-learning style-transfer styletransfer
Last synced: 3 months ago
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The style transfer paper collection in International CV conference
Host: GitHub
URL: https://github.com/neuralchen/awesome_style_transfer
Owner: neuralchen
License: mit
Created: 2021-06-22T08:20:24.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2022-09-06T16:13:46.000Z (about 2 years ago)
Last Synced: 2024-05-23T06:38:55.577Z (5 months ago)
Topics: awesome, awesome-list, deep-learning, style-transfer, styletransfer
Homepage:
Size: 36.1 KB
Stars: 81
Watchers: 9
Forks: 11
Open Issues: 0
Metadata Files:
- Readme: Readme.md
- License: LICENSE
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ultimate-awesome - awesome_style_transfer - The style transfer paper collection in International CV conference. (Other Lists / PowerShell Lists)
README

        # Paper list of Style Transfer

## ***Continuously updating***

## Ours style transfer paper

- Anisotropic Stroke Control for Multiple Artists Style Transfer

[[github]](https://github.com/neuralchen/ASMAGAN) [[paper]](https://arxiv.org/abs/2010.08175)

## The greatest style transfer papers

- A Neural Algorithm of Artistic Style

[[paper]](https://arxiv.org/pdf/1508.06576.pdf)

- Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

[[paper]](https://arxiv.org/pdf/1703.06868.pdf)

- Perceptual Losses for Real-Time Style Transfer and Super-Resolution

[[paper]](https://arxiv.org/pdf/1603.08155.pdf)

- A Style-Aware Content Loss for Real-time HD Style Transfer

[[paper]](https://openaccess.thecvf.com/content_ECCV_2018/papers/Artsiom_Sanakoyeu_A_Style-aware_Content_ECCV_2018_paper.pdf)

- Fast Patch-based Style Transfer of Arbitrary Style

[[paper]](https://arxiv.org/pdf/1612.04337.pdf)

## CVPR2022

- Splicing ViT Features for Semantic Appearance Transfer

[[paper]](https://arxiv.org/pdf/2201.00424.pdf)

- StyleMesh: Style Transfer for Indoor 3D Scene Reconstructions

[[paper]](https://arxiv.org/pdf/2112.01530.pdf)

- Unpaired Cartoon Image Synthesis via Gated Cycle Mapping

[[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Men_Unpaired_Cartoon_Image_Synthesis_via_Gated_Cycle_Mapping_CVPR_2022_paper.pdf)

- Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer

[[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Yang_Pastiche_Master_Exemplar-Based_High-Resolution_Portrait_Style_Transfer_CVPR_2022_paper.pdf)

- StyTr2: Image Style Transfer With Transformers

[[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Deng_StyTr2_Image_Style_Transfer_With_Transformers_CVPR_2022_paper.pdf)

- PCA-Based Knowledge Distillation Towards Lightweight and Content-Style Balanced Photorealistic Style Transfer Models

[[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Chiu_PCA-Based_Knowledge_Distillation_Towards_Lightweight_and_Content-Style_Balanced_Photorealistic_Style_CVPR_2022_paper.pdf)

- Industrial Style Transfer With Large-Scale Geometric Warping and Content Preservation

[[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Yang_Industrial_Style_Transfer_With_Large-Scale_Geometric_Warping_and_Content_Preservation_CVPR_2022_paper.pdf)

- CLIPstyler: Image Style Transfer With a Single Text Condition

[[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Kwon_CLIPstyler_Image_Style_Transfer_With_a_Single_Text_Condition_CVPR_2022_paper.pdf)

- Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

[[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_Exact_Feature_Distribution_Matching_for_Arbitrary_Style_Transfer_and_Domain_CVPR_2022_paper.pdf)

- StyleMesh: Style Transfer for Indoor 3D Scene Reconstructions

[[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Hollein_StyleMesh_Style_Transfer_for_Indoor_3D_Scene_Reconstructions_CVPR_2022_paper.pdf)

- Artistic Style Discovery with Independent Components

[[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Xie_Artistic_Style_Discovery_With_Independent_Components_CVPR_2022_paper.pdf)

## ICCV2021

- Learning to Stylize Novel Views 

[[paper]](https://arxiv.org/pdf/2105.13509.pdf)

- StyleFormer: Real-time Arbitrary Style Transfer via Parametric Style Composition

[[paper]](https://openaccess.thecvf.com/content/ICCV2021/papers/Wu_StyleFormer_Real-Time_Arbitrary_Style_Transfer_via_Parametric_Style_Composition_ICCV_2021_paper.pdf)

- Diverse Image Style Transfer via Invertible Cross-Space Mapping

[[paper]](https://openaccess.thecvf.com/content/ICCV2021/papers/Chen_Diverse_Image_Style_Transfer_via_Invertible_Cross-Space_Mapping_ICCV_2021_paper.pdf)

- DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer

[[paper]](https://openaccess.thecvf.com/content/ICCV2021/papers/Xu_DRB-GAN_A_Dynamic_ResBlock_Generative_Adversarial_Network_for_Artistic_Style_ICCV_2021_paper.pdf)

- Domain-Aware Universal Style Transfer

[[paper]](https://openaccess.thecvf.com/content/ICCV2021/papers/Hong_Domain-Aware_Universal_Style_Transfer_ICCV_2021_paper.pdf)

- 3DStyleNet: Creating 3D Shapes with Geometric and Texture Style Variations (It is another kind of style transfer)

[[paper]](https://openaccess.thecvf.com/content/ICCV2021/papers/Yin_3DStyleNet_Creating_3D_Shapes_With_Geometric_and_Texture_Style_Variations_ICCV_2021_paper.pdf)

- ALADIN: All Layer Adaptive Instance Normalization for Fine-grained Style Similarity

[[paper]](https://openaccess.thecvf.com/content/ICCV2021/papers/Ruta_ALADIN_All_Layer_Adaptive_Instance_Normalization_for_Fine-Grained_Style_Similarity_ICCV_2021_paper.pdf)

- Manifold Alignment for Semantically Aligned Style Transfer

[[paper]](https://openaccess.thecvf.com/content/ICCV2021/papers/Huo_Manifold_Alignment_for_Semantically_Aligned_Style_Transfer_ICCV_2021_paper.pdf)

- AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

[[paper]](https://openaccess.thecvf.com/content/ICCV2021/papers/Liu_AdaAttN_Revisit_Attention_Mechanism_in_Arbitrary_Neural_Style_Transfer_ICCV_2021_paper.pdf)

- StarEnhancer: Learning Real-Time and Style-Aware Image Enhancement (It is another kind of style transfer)

[[paper]](https://openaccess.thecvf.com/content/ICCV2021/papers/Song_StarEnhancer_Learning_Real-Time_and_Style-Aware_Image_Enhancement_ICCV_2021_paper.pdf)

## CVPR2021

- In the Light of Feature Distributions: Moment Matching for Neural Style Transfer

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Kalischek_In_the_Light_of_Feature_Distributions_Moment_Matching_for_Neural_CVPR_2021_paper.html)

- Style-Aware Normalized Loss for Improving Arbitrary Style Transfer

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Cheng_Style-Aware_Normalized_Loss_for_Improving_Arbitrary_Style_Transfer_CVPR_2021_paper.html)

- Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Kotovenko_Rethinking_Style_Transfer_From_Pixels_to_Parameterized_Brushstrokes_CVPR_2021_paper.html)

- Adaptive Convolutions for Structure-Aware Style Transfer

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Chandran_Adaptive_Convolutions_for_Structure-Aware_Style_Transfer_CVPR_2021_paper.html)

- ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/An_ArtFlow_Unbiased_Image_Style_Transfer_via_Reversible_Neural_Flows_CVPR_2021_paper.html)

- Rethinking and Improving the Robustness of Image Style Transfer **(Best Paper Candidate)**

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Wang_Rethinking_and_Improving_the_Robustness_of_Image_Style_Transfer_CVPR_2021_paper.html)

- Learning To Warp for Style Transfer

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Liu_Learning_To_Warp_for_Style_Transfer_CVPR_2021_paper.html)

- Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Lin_Drafting_and_Revision_Laplacian_Pyramid_Network_for_Fast_High-Quality_Artistic_CVPR_2021_paper.html)

- DualAST: Dual Style-Learning Networks for Artistic Style Transfer

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Chen_DualAST_Dual_Style-Learning_Networks_for_Artistic_Style_Transfer_CVPR_2021_paper.html)

- What Can Style Transfer and Paintings Do for Model Robustness?

[[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Lin_What_Can_Style_Transfer_and_Paintings_Do_for_Model_Robustness_CVPR_2021_paper.html)

## WACV2021

- Real-Time Localized Photorealistic Video Style Transfer

[[paper]](https://openaccess.thecvf.com/content/WACV2021/html/Xia_Real-Time_Localized_Photorealistic_Video_Style_Transfer_WACV_2021_paper.html)

- Style Transfer by Rigid Alignment in Neural Net Feature Space

[[paper]](https://openaccess.thecvf.com/content/WACV2021/html/Hada_Style_Transfer_by_Rigid_Alignment_in_Neural_Net_Feature_Space_WACV_2021_paper.html)

- Deep Preset: Blending and Retouching Photos With Color Style Transfer

[[paper]](https://openaccess.thecvf.com/content/WACV2021/html/Ho_Deep_Preset_Blending_and_Retouching_Photos_With_Color_Style_Transfer_WACV_2021_paper.html)

- Exploiting Spatial Relation for Reducing Distortion in Style Transfer

[[paper]](https://openaccess.thecvf.com/content/WACV2021/html/Chang_Exploiting_Spatial_Relation_for_Reducing_Distortion_in_Style_Transfer_WACV_2021_paper.html)

- Deep Preset: Blending and Retouching Photos With Color Style Transfer

[[paper]](https://openaccess.thecvf.com/content/WACV2021/html/Ho_Deep_Preset_Blending_and_Retouching_Photos_With_Color_Style_Transfer_WACV_2021_paper.html)

## CVPR2020

- Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer

[[paper]](https://openaccess.thecvf.com/content_CVPR_2020/html/Svoboda_Two-Stage_Peer-Regularized_Feature_Recombination_for_Arbitrary_Image_Style_Transfer_CVPR_2020_paper.html)

- Collaborative Distillation for Ultra-Resolution Universal Style Transfer

[[paper]](https://openaccess.thecvf.com/content_CVPR_2020/html/Wang_Collaborative_Distillation_for_Ultra-Resolution_Universal_Style_Transfer_CVPR_2020_paper.html)

## ECCV2020

- Filter Style Transfer between Photos

[[paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4809_ECCV_2020_paper.php)

- Optical Flow Distillation: Towards Efficient and Stable Video Style Transfer

[[paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/13_ECCV_2020_paper.php)

- Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer

[[paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/575_ECCV_2020_paper.php)

- Domain-Specific Mappings for Generative Adversarial Style Transfer

[[paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/634_ECCV_2020_paper.php)

- Iterative Feature Transformation for Fast and Versatile Universal Style Transfer

[[paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3170_ECCV_2020_paper.php)

- Deformable Style Transfer

[[paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5333_ECCV_2020_paper.php)

## ICCV2019

- Content and Style Disentanglement for Artistic Style Transfer

[[paper]](https://openaccess.thecvf.com/content_ICCV_2019/html/Kotovenko_Content_and_Style_Disentanglement_for_Artistic_Style_Transfer_ICCV_2019_paper.html)

- Understanding Generalized Whitening and Coloring Transform for Universal Style Transfer

[[paper]](https://openaccess.thecvf.com/content_ICCV_2019/html/Chiu_Understanding_Generalized_Whitening_and_Coloring_Transform_for_Universal_Style_Transfer_ICCV_2019_paper.html)

- Multimodal Style Transfer via Graph Cuts

[[paper]](https://openaccess.thecvf.com/content_ICCV_2019/html/Zhang_Multimodal_Style_Transfer_via_Graph_Cuts_ICCV_2019_paper.html)

- A Closed-Form Solution to Universal Style Transfer

[[paper]](https://openaccess.thecvf.com/content_ICCV_2019/html/Lu_A_Closed-Form_Solution_to_Universal_Style_Transfer_ICCV_2019_paper.html)

- Photorealistic Style Transfer via Wavelet Transforms

[[paper]](https://openaccess.thecvf.com/content_ICCV_2019/html/Yoo_Photorealistic_Style_Transfer_via_Wavelet_Transforms_ICCV_2019_paper.html)

## CVPR2019

- Attention-Aware Multi-Stroke Style Transfer

[[paper]](https://openaccess.thecvf.com/content_CVPR_2019/html/Yao_Attention-Aware_Multi-Stroke_Style_Transfer_CVPR_2019_paper.html)

- Arbitrary Style Transfer With Style-Attentional Networks

[[paper]](https://openaccess.thecvf.com/content_CVPR_2019/html/Park_Arbitrary_Style_Transfer_With_Style-Attentional_Networks_CVPR_2019_paper.html)

- A Flexible Convolutional Solver for Fast Style Transfers

[[paper]](https://openaccess.thecvf.com/content_CVPR_2019/html/Puy_A_Flexible_Convolutional_Solver_for_Fast_Style_Transfers_CVPR_2019_paper.html)

- A Content Transformation Block for Image Style Transfer

[[paper]](https://openaccess.thecvf.com/content_CVPR_2019/html/Kotovenko_A_Content_Transformation_Block_for_Image_Style_Transfer_CVPR_2019_paper.html)

- Style Transfer by Relaxed Optimal Transport and Self-Similarity

[[paper]](https://openaccess.thecvf.com/content_CVPR_2019/html/Kolkin_Style_Transfer_by_Relaxed_Optimal_Transport_and_Self-Similarity_CVPR_2019_paper.html)

## CVPR2018

- Stereoscopic Neural Style Transfer

[[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Stereoscopic_Neural_Style_CVPR_2018_paper.pdf)

- Multi-Content GAN for Few-Shot Font Style Transfer

[[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Azadi_Multi-Content_GAN_for_CVPR_2018_paper.pdf)

- Neural Style Transfer via Meta Networks

[[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Neural_Style_Transfer_CVPR_2018_paper.pdf)

- Arbitrary Style Transfer With Deep Feature Reshuffle

[[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Gu_Arbitrary_Style_Transfer_CVPR_2018_paper.pdf)

- Avatar-Net: Multi-Scale Zero-Shot Style Transfer by Feature Decoration

[[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Sheng_Avatar-Net_Multi-Scale_Zero-Shot_CVPR_2018_paper.pdf)

- Separating Style and Content for Generalized Style Transfer

[[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Separating_Style_and_CVPR_2018_paper.pdf)

## ICCV2017

- Coherent Online Video Style Transfer

[[paper]](https://openaccess.thecvf.com/content_ICCV_2017/papers/Chen_Coherent_Online_Video_ICCV_2017_paper.pdf)

- Arbitrary Style Transfer in Real-Time With Adaptive Instance Normalization

[[paper]](https://openaccess.thecvf.com/content_ICCV_2017/papers/Huang_Arbitrary_Style_Transfer_ICCV_2017_paper.pdf)

- Decoder Network Over Lightweight Reconstructed Feature for Fast Semantic Style Transfer

[[paper]](https://openaccess.thecvf.com/content_ICCV_2017/papers/Lu_Decoder_Network_Over_ICCV_2017_paper.pdf)

- Sketching With Style: Visual Search With Sketches and Aesthetic Context

[[paper]](https://openaccess.thecvf.com/content_ICCV_2017/papers/Collomosse_Sketching_With_Style_ICCV_2017_paper.pdf)

- Characterizing and Improving Stability in Neural Style Transfer

[[paper]](https://openaccess.thecvf.com/content_ICCV_2017/papers/Gupta_Characterizing_and_Improving_ICCV_2017_paper.pdf)

## CVPR2017

- Real-Time Neural Style Transfer for Videos

[[paper]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Huang_Real-Time_Neural_Style_CVPR_2017_paper.pdf)

- StyleBank: An Explicit Representation for Neural Image Style Transfer

[[paper]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Chen_StyleBank_An_Explicit_CVPR_2017_paper.pdf)

- Controlling Perceptual Factors in Neural Style Transfer

[[paper]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Gatys_Controlling_Perceptual_Factors_CVPR_2017_paper.pdf)

- Deep Photo Style Transfer

[[paper]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Luan_Deep_Photo_Style_CVPR_2017_paper.pdf)

- Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer

[[paper]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Wang_Multimodal_Transfer_A_CVPR_2017_paper.pdf)