https://github.com/i2-multimedia-lab/diffusest
공식 코드DiffuseST: Unleashing the Capability of the Diffusion Model for Style Transfer
Papers with Code 아카이브
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/iamalexkorotin/Wasserstein2GenerativeNetworks
공식 코드https://github.com/ianxmason/local-phases
공식 코드https://github.com/iglict/stylizednerf
공식 코드StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning
https://github.com/iiscleap/zest
공식 코드Zero Shot Audio to Audio Emotion Transfer With Speaker Disentanglement
https://github.com/iit-pavis/learnaug-uda
공식 코드Learnable Data Augmentation for One-Shot Unsupervised Domain Adaptation
https://github.com/ilyagusev/rudetox
공식 코드https://github.com/instantx-research/instantstyle-plus
공식 코드InstantStyle-Plus: Style Transfer with Content-Preserving in Text-to-Image Generation
https://github.com/isi-nlp/astrapop
공식 코드https://github.com/isi-nlp/stamp
공식 코드https://github.com/isrugeek/semcolour
공식 코드Nanoscale Microscopy Images Colorization Using Neural Networks
https://github.com/itsss/img2img_sa
공식 코드Unsupervised Image-to-Image Translation with Self-Attention Networks
https://github.com/ivanmontero/autobot
공식 코드Sentence Bottleneck Autoencoders from Transformer Language Models
https://github.com/izhanvarsky/vectornst
공식 코드https://github.com/jakezhaojb/ARAE
공식 코드https://github.com/jamie-cheung/artbank
공식 코드ArtBank: Artistic Style Transfer with Pre-trained Diffusion Model and Implicit Style Prompt Bank
https://github.com/jamie-cheung/lsast
공식 코드https://github.com/jankowskichristopher/red-teaming-segment-anything-model
공식 코드https://github.com/jarek-pawlowski/microbial-dataset-generation
공식 코드Generation of microbial colonies dataset with deep learning style transfer
https://github.com/jayoungkim408/sos
공식 코드https://github.com/jayparanjape/f-vita
공식 코드F-ViTA: Foundation Model Guided Visible to Thermal Translation
https://github.com/jcyang98/inst
공식 코드Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation
https://github.com/jeremyxsc/finegpr
공식 코드Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification
https://github.com/jhtonykoo/music_mixing_style_transfer
공식 코드Music Mixing Style Transfer: A Contrastive Learning Approach to Disentangle Audio Effects
https://github.com/jiashunwang/Neural-Pose-Transfer
공식 코드Neural Pose Transfer by Spatially Adaptive Instance Normalization
https://github.com/jiechen2358/VirtualFittingRoom
공식 코드https://github.com/jiwoogit/StyleID
공식 코드https://github.com/johannwyh/styleinv
공식 코드StyleInV: A Temporal Style Modulated Inversion Network for Unconditional Video Generation
https://github.com/jonhare/DifferentiableSketching
공식 코드https://github.com/josephcao0327/stylefool
공식 코드StyleFool: Fooling Video Classification Systems via Style Transfer
https://github.com/judydnguyen/pardon-feddg
공식 코드PARDON: Privacy-Aware and Robust Federated Domain Generalization
https://github.com/junhocho/paired-glyph-matching
공식 코드https://github.com/junleen/RainNet
공식 코드Region-aware Adaptive Instance Normalization for Image Harmonization
https://github.com/junyanz/CycleGAN
공식 코드Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
공식 코드Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/juseonghan/meshbrush
공식 코드MeshBrush: Painting the Anatomical Mesh with Neural Stylization for Endoscopy
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.