https://github.com/bdehaine/SinGan
SinGAN: Learning a Generative Model from a Single Natural Image
Papers with Code 아카이브
Image Manipulation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 1
- 보존된 평가 기록
- 2
Image Manipulation is the process of altering or transforming an existing image to achieve a desired effect or to modify its content. This can involve various techniques and tools to enhance, modify, or create images based on specific requirements.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/bennyqp/artificial-inspiration
SinGAN: Learning a Generative Model from a Single Natural Image
https://github.com/brenoskuk/recvis
SinGAN: Learning a Generative Model from a Single Natural Image
https://github.com/cal-app/slow-NST
https://github.com/cassiePython/cddfm3d
Cross-Domain and Disentangled Face Manipulation with 3D Guidance
https://github.com/charlescheng0117/p2pvg
https://github.com/chjw1475/localbasis
Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs
https://github.com/cloneofsimo/lora
https://github.com/cryu854/SinGAN
SinGAN: Learning a Generative Model from a Single Natural Image
https://github.com/cs-giung/FSRNet-pytorch
MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
https://github.com/cuixing100876/instastyle
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
https://github.com/dddb11/MVSS-Net
Image Manipulation Detection by Multi-View Multi-Scale Supervision
https://github.com/dkn16/stylegan2-pytorch
https://github.com/dmcv-ecnu/MindSpore_ModelZoo/tree/main/SinGanMindspore
SinGAN: Learning a Generative Model from a Single Natural Image
https://github.com/dome272/MaskGIT-pytorch
https://github.com/dstein64/pastiche
https://github.com/ducminhkhoi/Amodal-Instance-Seg-ASBU
https://github.com/ehsannowroozi/RDFS
https://github.com/eladrich/pixel2style2pixel
https://github.com/erenovic/SADIM
https://github.com/facebookresearch/msn
High Fidelity Visualization of What Your Self-Supervised Representation Knows About
https://github.com/fengpings/Two-branch-Document-Recapture
Two-branch Multi-scale Deep Neural Network for Generalized Document Recapture Attack Detection
https://github.com/friedmanroy/hi-generation
SRFlow: Learning the Super-Resolution Space with Normalizing Flow
https://github.com/futscdav/Chunkmogrify
https://github.com/garibida/ReNoise-Inversion
https://github.com/genforce/interfacegan
Interpreting the Latent Space of GANs for Semantic Face Editing
https://github.com/genforce/sefa
https://github.com/google-research/sparf
Learning Accurate Dense Correspondences and When to Trust Them
https://github.com/guillermogotre/cusp
https://github.com/happy-jihye/Cartoon-StyleGAN
https://github.com/happy-jihye/Cartoon-StyleGan2
https://github.com/huggingface/diffusers
Versatile Diffusion: Text, Images and Variations All in One Diffusion Model
https://github.com/icey-zhang/paddle_SinGAN
SinGAN: Learning a Generative Model from a Single Natural Image
https://github.com/iigroup/mm-celeba-hq-dataset
Conditional Image Generation and Manipulation for User-Specified Content
https://github.com/ilyak93/SinGan
SinGAN: Learning a Generative Model from a Single Natural Image
https://github.com/ilyak93/SinGanF2
SinGAN: Learning a Generative Model from a Single Natural Image
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.