https://github.com/litterbrother-xiao/overview-of-non-autoregressive-applications
공식 코드A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond
Papers with Code 아카이브
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/liusongxiang/StarGAN-Voice-Conversion
공식 코드AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
https://github.com/lkeab/gaussian-grouping
공식 코드https://github.com/lkpengcs/dcda
공식 코드https://github.com/llnl/luar
공식 코드Can Authorship Representation Learning Capture Stylistic Features?
https://github.com/lsx0101/Instant-NeRF-Stylization
공식 코드https://github.com/lu-m13/OptimalStyleTransfer
공식 코드https://github.com/luanfujun/deep-photo-styletransfer
공식 코드https://github.com/lukasHoel/stylemesh
공식 코드StyleMesh: Style Transfer for Indoor 3D Scene Reconstructions
https://github.com/luo-lorry/Stylized-Medical-Segmentation
공식 코드Structure-Aware Stylized Image Synthesis for Robust Medical Image Segmentation
https://github.com/lvyiwei1/StylePTB
공식 코드StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
https://github.com/lvyiwei1/diffuseq_styleptb
공식 코드Fine-grained Text Style Transfer with Diffusion-Based Language Models
https://github.com/machelreid/editpro
공식 코드https://github.com/machelreid/lewis
공식 코드LEWIS: Levenshtein Editing for Unsupervised Text Style Transfer
https://github.com/maciej3031/comixify
공식 코드https://github.com/magenta/magenta/blob/master/magenta/models/arbitrary_image_stylization/README.md
공식 코드Exploring the structure of a real-time, arbitrary neural artistic stylization network
https://github.com/mahmoudnafifi/color-aware-style-transfer
공식 코드https://github.com/majedelhelou/VIDIT
공식 코드https://github.com/manga-uofa/prompt-edit
공식 코드https://github.com/manuelruder/artistic-videos
공식 코드https://github.com/manuelruder/fast-artistic-videos
공식 코드https://github.com/manugar/imagestyletransfer
공식 코드https://github.com/mariodoebler/test-time-adaptation
공식 코드Introducing Intermediate Domains for Effective Self-Training during Test-Time
https://github.com/martiansideofthemoon/style-transfer-paraphrase
공식 코드Reformulating Unsupervised Style Transfer as Paraphrase Generation
https://github.com/masud99r/thinker
공식 코드https://github.com/matthias-wright/art-fid
공식 코드https://github.com/mazurowski-lab/breastMRI_styletransfer
공식 코드Deep Learning for Breast MRI Style Transfer with Limited Training Data
https://github.com/mchong6/JoJoGAN
공식 코드https://github.com/medicl-vu/crossmoda2023
공식 코드Learning Site-specific Styles for Multi-institutional Unsupervised Cross-modality Domain Adaptation
https://github.com/megvii-research/megactor
공식 코드MegActor: Harness the Power of Raw Video for Vivid Portrait Animation
https://github.com/megvii-research/megfaceanimate
공식 코드MegActor: Harness the Power of Raw Video for Vivid Portrait Animation
https://github.com/menyifang/dct-net
공식 코드DCT-Net: Domain-Calibrated Translation for Portrait Stylization
https://github.com/michelecafagna26/CHANGE-IT
공식 코드On the interaction of automatic evaluation and task framing in headline style transfer
https://github.com/michiyasunaga/bifi
공식 코드https://github.com/mikasenghaas/sillystill
공식 코드https://github.com/milesigel/audio-sentiment-transfer
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.