Papers with Code 아카이브

Video Style Transfer

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/JarrentWu1031/CCPL

공식 코드

CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer

https://github.com/NevSNev/UniST

공식 코드

Two Birds, One Stone: A Unified Framework for Joint Learning of Image and Video Style Transfers

https://github.com/QuanjianSong/UniVST

공식 코드

UniVST: A Unified Framework for Training-free Localized Video Style Transfer

https://github.com/chenyangqiqi/fatezero

공식 코드

FateZero: Fusing Attentions for Zero-shot Text-based Video Editing

https://github.com/giddyyupp/wait

공식 코드

WAIT: Feature Warping for Animation to Illustration video Translation using GANs

https://github.com/haha-lisa/style-a-video

공식 코드

Style-A-Video: Agile Diffusion for Arbitrary Text-based Video Style Transfer

https://github.com/huage001/adaattn

공식 코드

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

https://github.com/linfengWen98/CAP-VSTNet

공식 코드

CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer

https://github.com/weifeng-chen/control-a-video

공식 코드

Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback Learning

https://github.com/williamyang1991/vtoonify

공식 코드

VToonify: Controllable High-Resolution Portrait Video Style Transfer

https://github.com/wzmsltw/adaattn

공식 코드

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

https://github.com/CompVis/adaptive-style-transfer

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

https://github.com/EmptySamurai/pytorch-reconet

ReCoNet: Real-time Coherent Video Style Transfer Network

https://github.com/GuillaumeAI/rwml__adaptive_style_transfer

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

https://github.com/LeMU-Haruka/reconet-mindspore

ReCoNet: Real-time Coherent Video Style Transfer Network

https://github.com/Net-Mist/style-transfer-tf2

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

https://github.com/OfekCohen1/Style-On-3D-Video

ReCoNet: Real-time Coherent Video Style Transfer Network

https://github.com/Tonyhuiii/color-transform

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

https://github.com/Uemuet/style-transfer

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

https://github.com/Uemuet/styletransfer-adaptive

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

https://github.com/cristinecosta/CompVis

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

https://github.com/gaetano-signorelli/Attention-Style-Transfer

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

https://github.com/gunpowder1473/Adaptive-Style-Transfer-Tensorflow

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

https://github.com/irsisyphus/reconet

ReCoNet: Real-time Coherent Video Style Transfer Network

https://github.com/liulai/reconet-torch

ReCoNet: Real-time Coherent Video Style Transfer Network

https://github.com/safwankdb/ReCoNet-PyTorch

ReCoNet: Real-time Coherent Video Style Transfer Network

https://github.com/sundogai/style-transfer

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

https://github.com/thiagoambiel/NeuralAtlases

Layered Neural Atlases for Consistent Video Editing

https://github.com/xiuyu0000/papers_with_examples/tree/main/reconet

ReCoNet: Real-time Coherent Video Style Transfer Network

https://github.com/yangyucheng000/ReCoNet

ReCoNet: Real-time Coherent Video Style Transfer Network

https://github.com/ykasten/layered-neural-atlases

Layered Neural Atlases for Consistent Video Editing

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.