https://github.com/kingjamessong/fastdifferentiablematsqrt
공식 코드Fast Differentiable Matrix Square Root and Inverse Square Root
Papers with Code 아카이브
Drawing Pictures
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kornelhowil/clipgaussian
공식 코드CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splatting
https://github.com/kwanyun/LeGO_code
공식 코드https://github.com/laihuiyuan/Pre-trained-formality-transfer
공식 코드Thank you BART! Rewarding Pre-Trained Models Improves Formality Style Transfer
https://github.com/laihuiyuan/eval-formality-transfer
공식 코드Human Judgement as a Compass to Navigate Automatic Metrics for Formality Transfer
https://github.com/laihuiyuan/generic-resources-for-tst
공식 코드https://github.com/laihuiyuan/multilingual-tst
공식 코드Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer
https://github.com/lancopku/Augmented_Data_for_FST
공식 코드https://github.com/lbsswu/Chinese_style_transfer
공식 코드Neural Abstract Style Transfer for Chinese Traditional Painting
https://github.com/ldzhangyx/vis2mus
공식 코드Vis2Mus: Exploring Multimodal Representation Mapping for Controllable Music Generation
https://github.com/leongatys/NeuralImageSynthesis
공식 코드https://github.com/lephuoccat/Supervised-Encoding-Quantizer
공식 코드https://github.com/lijuncen/Sentiment-and-Style-Transfer
공식 코드Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer
https://github.com/limingcv/Photorealistic-Style-Transfer
공식 코드https://github.com/linear95/rlm
공식 코드https://github.com/linfengWen98/CAP-VSTNet
공식 코드CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer
https://github.com/linllll/maskst
공식 코드https://github.com/linnanwang/AlphaX-NASBench101
공식 코드AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search
https://github.com/lishaoxu1994/diffstyler
공식 코드https://github.com/lishaoxu1994/instant-nerf-stylization
공식 코드https://github.com/litterbrother-xiao/overview-of-non-autoregressive-applications
공식 코드A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond
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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.