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Drawing Pictures

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

https://github.com/mahmoudnafifi/color-aware-style-transfer

공식 코드

CAMS: Color-Aware Multi-Style Transfer

https://github.com/majedelhelou/VIDIT

공식 코드

NTIRE 2021 Depth Guided Image Relighting Challenge

https://github.com/manga-uofa/prompt-edit

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Prompt-Based Editing for Text Style Transfer

https://github.com/manuelruder/artistic-videos

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Artistic style transfer for videos

https://github.com/manuelruder/fast-artistic-videos

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Artistic style transfer for videos and spherical images

https://github.com/manugar/imagestyletransfer

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Neural Style Transfer and Unpaired Image-to-Image Translation to deal with the Domain Shift Problem on Spheroid Segmentation

https://github.com/mariodoebler/test-time-adaptation

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Introducing Intermediate Domains for Effective Self-Training during Test-Time

https://github.com/martiansideofthemoon/style-transfer-paraphrase

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Reformulating Unsupervised Style Transfer as Paraphrase Generation

https://github.com/masud99r/thinker

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Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning

https://github.com/matthias-wright/art-fid

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ArtFID: Quantitative Evaluation of Neural Style Transfer

https://github.com/mazurowski-lab/breastMRI_styletransfer

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Deep Learning for Breast MRI Style Transfer with Limited Training Data

https://github.com/mchong6/JoJoGAN

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JoJoGAN: One Shot Face Stylization

https://github.com/medicl-vu/crossmoda2023

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Learning Site-specific Styles for Multi-institutional Unsupervised Cross-modality Domain Adaptation

https://github.com/megvii-research/megactor

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MegActor: Harness the Power of Raw Video for Vivid Portrait Animation

https://github.com/megvii-research/megfaceanimate

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MegActor: Harness the Power of Raw Video for Vivid Portrait Animation

https://github.com/menyifang/dct-net

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DCT-Net: Domain-Calibrated Translation for Portrait Stylization

https://github.com/michelecafagna26/CHANGE-IT

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On the interaction of automatic evaluation and task framing in headline style transfer

https://github.com/michiyasunaga/bifi

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Break-It-Fix-It: Unsupervised Learning for Program Repair

https://github.com/mikasenghaas/sillystill

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CNNs for Style Transfer of Digital to Film Photography

https://github.com/milesigel/audio-sentiment-transfer

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Music Sentiment Transfer

https://github.com/mindspore-lab/mindediting

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Tunable Convolutions with Parametric Multi-Loss Optimization

https://github.com/mingkaid/rl-prompt

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RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning

https://github.com/mingsun-tse/collaborative-distillation

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Collaborative Distillation for Ultra-Resolution Universal Style Transfer

https://github.com/mingzi151/interpretationdata

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It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpretation Data

https://github.com/mireshghallah/style-pooling

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Style Pooling: Automatic Text Style Obfuscation for Improved Classification Fairness

https://github.com/monkeyseedocg/momo-code

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Monkey See, Monkey Do: Harnessing Self-attention in Motion Diffusion for Zero-shot Motion Transfer

https://github.com/mrzzy2021/styledmotionsynthesis

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Unifying Human Motion Synthesis and Style Transfer with Denoising Diffusion Probabilistic Models

https://github.com/msracver/Style-Feature-Reshuffle

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Arbitrary Style Transfer with Deep Feature Reshuffle

https://github.com/multimedialabsfu/learned-point-cloud-compression-for-classification

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Learned Compression for Images and Point Clouds

https://github.com/multimodal-art-projection/yue

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YuE: Scaling Open Foundation Models for Long-Form Music Generation

https://github.com/nadavc220/semanticsegmentationinartpaintings

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Semantic Segmentation in Art Paintings

https://github.com/nadeemlab/deepliif

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An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment

https://github.com/naver-ai/Visual-Style-Prompting

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Visual Style Prompting with Swapping Self-Attention

https://github.com/nazmul-karim170/Free-Editor

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Free-Editor: Zero-shot Text-driven 3D Scene Editing

https://github.com/nazmul-karim170/save-tex2video

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SAVE: Spectral-Shift-Aware Adaptation of Image Diffusion Models for Text-driven Video Editing

https://github.com/nbalepur/text-fact-transfer

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Text Fact Transfer

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