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

https://github.com/scjjb/midog_domain_adaptation

공식 코드

Assessing domain adaptation techniques for mitosis detection in multi-scanner breast cancer histopathology images

https://github.com/semchan/NLUT

공식 코드

NLUT: Neural-based 3D Lookup Tables for Video Photorealistic Style Transfer

https://github.com/semchan/UPST-NeRF

공식 코드

UPST-NeRF: Universal Photorealistic Style Transfer of Neural Radiance Fields for 3D Scene

https://github.com/seq-to-mind/semi-style-transfer

공식 코드

Learning from Bootstrapping and Stepwise Reinforcement Reward: A Semi-Supervised Framework for Text Style Transfer

https://github.com/shahaf1313/procst

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ProCST: Boosting Semantic Segmentation Using Progressive Cyclic Style-Transfer

https://github.com/shallinan1/steerstyletransfer

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STEER: Unified Style Transfer with Expert Reinforcement

https://github.com/shaojintian/power_law_decay

공식 코드

Power-Law Decay Loss for Large Language Model Finetuning: Focusing on Information Sparsity to Enhance Generation Quality

https://github.com/sharan21/epaae

공식 코드

Towards Robust and Semantically Organised Latent Representations for Unsupervised Text Style Transfer

https://github.com/shashankvkt/alignmixup_cvpr22

공식 코드

AlignMixup: Improving Representations By Interpolating Aligned Features

https://github.com/shengliu66/icv

공식 코드

In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering

https://github.com/shentianxiao/language-style-transfer

공식 코드

Style Transfer from Non-Parallel Text by Cross-Alignment

https://github.com/shentianxiao/text-autoencoders

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Educating Text Autoencoders: Latent Representation Guidance via Denoising

https://github.com/shouvikmani/edge-colorizer

공식 코드

Artistic Enhancement and Style Transfer of Image Edges using Directional Pseudo-coloring

https://github.com/showlab/PhotoDoodle

공식 코드

PhotoDoodle: Learning Artistic Image Editing from Few-Shot Pairwise Data

https://github.com/showlab/Tune-A-Video

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Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation

https://github.com/showlab/omniconsistency

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OmniConsistency: Learning Style-Agnostic Consistency from Paired Stylization Data

https://github.com/shrimai/Style-Transfer-Through-Back-Translation

공식 코드

Style Transfer Through Back-Translation

https://github.com/shs910/psst

공식 코드

PSST: A Benchmark for Evaluation-driven Text Public-Speaking Style Transfer

https://github.com/shs910/tsst

공식 코드

PSST: A Benchmark for Evaluation-driven Text Public-Speaking Style Transfer

https://github.com/silky1708/local-style-transfer

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LEAST: "Local" text-conditioned image style transfer

https://github.com/silvia1993/HyMOS

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Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation

https://github.com/sinmdm/sinmdm

공식 코드

Single Motion Diffusion

https://github.com/siyuhuang/quantart

공식 코드

QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity

https://github.com/sjtuplayer/compositional_neural_painter

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Stroke-based Neural Painting and Stylization with Dynamically Predicted Painting Region

https://github.com/skoltech-nlp/detox

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Text Detoxification using Large Pre-trained Neural Models

https://github.com/skoltech-nlp/formality

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Detecting Text Formality: A Study of Text Classification Approaches

https://github.com/skoltech-nlp/multilingual_detox

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Exploring Cross-lingual Textual Style Transfer with Large Multilingual Language Models

https://github.com/skoltech-nlp/rudetoxifier

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Methods for Detoxification of Texts for the Russian Language

https://github.com/skoltech-nlp/sgdd-tst

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Studying the role of named entities for content preservation in text style transfer

https://github.com/songrise/Artist

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DiffArtist: Towards Structure and Appearance Controllable Image Stylization

https://github.com/songrise/mllm4art

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Multimodal LLMs Can Reason about Aesthetics in Zero-Shot

https://github.com/sonnguyen129/deep-feature-rotation

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Deep Feature Rotation for Multimodal Image Style Transfer

https://github.com/sooyyoungg/aesfa

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AesFA: An Aesthetic Feature-Aware Arbitrary Neural Style Transfer

https://github.com/sophiajw/HistAuGAN

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Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations

https://github.com/souro/multilingual_text_detoxification

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Text Detoxification as Style Transfer in English and Hindi

https://github.com/souro/multilingual_tst

공식 코드

Multilingual Text Style Transfer: Datasets & Models for Indian Languages

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