https://github.com/MartinBuessemeyer/Artistic-Texture-Control
공식 코드Controlling Geometric Abstraction and Texture for Artistic Images
Papers with Code 아카이브
Text-based Image Editing
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Nose should be sharped and lips should be less fat
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MichalGeyer/plug-and-play
공식 코드Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation
https://github.com/Null-0000/ViMAEdit
공식 코드Vision-guided and Mask-enhanced Adaptive Denoising for Prompt-based Image Editing
https://github.com/RotsteinNoam/Paint-by-Inpaint
공식 코드Paint by Inpaint: Learning to Add Image Objects by Removing Them First
https://github.com/Xilluill/KV-Edit
공식 코드KV-Edit: Training-Free Image Editing for Precise Background Preservation
https://github.com/cure-lab/directinversion
공식 코드Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
https://github.com/exx8/differential-diffusion
공식 코드https://github.com/google/prompt-to-prompt
공식 코드https://github.com/holmesshuan/fireflow
공식 코드FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
https://github.com/hwang1996/maniclip
공식 코드https://github.com/jingjiqinggong/specp2p
공식 코드SpecRef: A Fast Training-free Baseline of Specific Reference-Condition Real Image Editing
https://github.com/kookie12/FlexiEdit
공식 코드FlexiEdit: Frequency-Aware Latent Refinement for Enhanced Non-Rigid Editing
https://github.com/pix2pixzero/pix2pix-zero
공식 코드https://github.com/rohitgandikota/erasing
공식 코드https://github.com/salesforce/HIVE
공식 코드HIVE: Harnessing Human Feedback for Instructional Visual Editing
https://github.com/salesforce/edict
공식 코드EDICT: Exact Diffusion Inversion via Coupled Transformations
https://github.com/sen-mao/StyleDiffusion
공식 코드StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing
https://github.com/shi-labs/versatile-diffusion
공식 코드Versatile Diffusion: Text, Images and Variations All in One Diffusion Model
https://github.com/sled-group/InfEdit
공식 코드https://github.com/snap-research/stable-flow
공식 코드https://github.com/tencentarc/masactrl
공식 코드MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editing
https://github.com/timothybrooks/instruct-pix2pix
공식 코드InstructPix2Pix: Learning to Follow Image Editing Instructions
https://github.com/virajprabhu/lance
공식 코드LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images
https://github.com/wangkai930418/DPL
공식 코드Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing
https://github.com/xuesong39/dac
공식 코드Doubly Abductive Counterfactual Inference for Text-based Image Editing
https://github.com/Muhammad-Huzaifaa/ObjectCompose
LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images
https://github.com/PaddlePaddle/PaddleNLP
Versatile Diffusion: Text, Images and Variations All in One Diffusion Model
https://github.com/Shilin-LU/TF-ICON
Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation
https://github.com/ZHO-ZHO-ZHO/ComfyUI-Differential_Diffusion-Workflows
https://github.com/alimohammadiamirhossein/cora
Cora: Correspondence-aware image editing using few step diffusion
https://github.com/bloc97/CrossAttentionControl
https://github.com/chenwu98/cycle-diffusion
https://github.com/cocktailpeanutlabs/differential-diffusion-ui
https://github.com/cure-lab/pnpinversion
Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
https://github.com/hansam95/nmg
https://github.com/huggingface/diffusers
Versatile Diffusion: Text, Images and Variations All in One Diffusion Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.