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Facial Editing

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평가표

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코드

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

https://github.com/FeiiYin/StyleHEAT

공식 코드

StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN

https://github.com/billyxyb/transeditor

공식 코드

TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing

https://github.com/danielroich/PTI

공식 코드

Pivotal Tuning for Latent-based Editing of Real Images

https://github.com/diffusion-facex/facex

공식 코드

A Generalist FaceX via Learning Unified Facial Representation

https://github.com/e4s2023/e4s2023

공식 코드

E4S: Fine-grained Face Swapping via Editing With Regional GAN Inversion

https://github.com/e4s2024/e4s2024

공식 코드

E4S: Fine-grained Face Swapping via Editing With Regional GAN Inversion

https://github.com/rotemtzaban/STIT

공식 코드

Stitch it in Time: GAN-Based Facial Editing of Real Videos

https://github.com/rshaojimmy/seqdeepfake

공식 코드

Detecting and Recovering Sequential DeepFake Manipulation

https://github.com/seasonSH/SemanticStyleGAN

공식 코드

SemanticStyleGAN: Learning Compositional Generative Priors for Controllable Image Synthesis and Editing

https://github.com/yumingj/talk-to-edit

공식 코드

Talk-to-Edit: Fine-Grained Facial Editing via Dialog

https://github.com/zeus1037/seed

공식 코드

SEED: A Benchmark Dataset for Sequential Facial Attribute Editing with Diffusion Models

https://github.com/zhixinshu/NeuralFaceEditing

공식 코드

Neural Face Editing with Intrinsic Image Disentangling

https://github.com/cloneofsimo/lora

Pivotal Tuning for Latent-based Editing of Real Images

https://github.com/futscdav/Chunkmogrify

Pivotal Tuning for Latent-based Editing of Real Images

https://github.com/kpahwa16/BioFacenet-Pytorch-Implementation

Neural Face Editing with Intrinsic Image Disentangling

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.