title: LEDITS: Real Image Editing with DDPM Inversion and Semantic Guidance
summary: Recent large-scale text-guided diffusion models provide powerful
  image-generation capabilities. Currently, a significant effort is given to
  enable the modification of these images using text only as means to offer
  intuitive and versatile editing. However, editing proves to be difficult for
  these generative models due to the inherent nature of editing techniques, which
  involves preserving certain content from the original image. Conversely, in
  text-based models, even minor modifications to the text prompt frequently
  result in an entirely distinct result, making attaining one-shot generation
  that accurately corresponds to the users intent exceedingly challenging. In
  addition, to edit a real image using these state-of-the-art tools, one must
  first invert the image into the pre-trained models domain - adding another
  factor affecting the edit quality, as well as latency. In this exploratory
  report, we propose LEDITS - a combined lightweight approach for real-image
  editing, incorporating the Edit Friendly DDPM inversion technique with Semantic
  Guidance, thus extending Semantic Guidance to real image editing, while
  harnessing the editing capabilities of DDPM inversion as well. This approach
  achieves versatile edits, both subtle and extensive as well as alterations in
  composition and style, while requiring no optimization nor extensions to the
  architecture.
paper_authors._id: 64a392bafbd6fdd06d7dfcac
paper_authors.name: Linoy Tsaban
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-07-04T07:54:34.268Z
paper_authors._id: 638f308fc4444c6ca870b60a
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/638f308fc4444c6ca870b60a/Q11NK-8-JbiilJ-vk2LAR.png
paper_authors.fullname: Linoy Tsaban
paper_authors.type: user
paper_authors.user: linoyts
paper_authors._id: 64a392bafbd6fdd06d7dfcad
paper_authors.name: Apolinário Passos
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-07-04T07:54:20.772Z
paper_authors._id: 624bebf604abc7ebb01789af
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1649143001781-624bebf604abc7ebb01789af.jpeg
paper_authors.fullname: Apolinário from multimodal AI art
paper_authors.type: user
paper_authors.user: multimodalart
paper_title: LEDITS: Real Image Editing with DDPM Inversion and Semantic Guidance
paper_summary: Recent large-scale text-guided diffusion models provide powerful
  image-generation capabilities. Currently, a significant effort is given to
  enable the modification of these images using text only as means to offer
  intuitive and versatile editing. However, editing proves to be difficult for
  these generative models due to the inherent nature of editing techniques, which
  involves preserving certain content from the original image. Conversely, in
  text-based models, even minor modifications to the text prompt frequently
  result in an entirely distinct result, making attaining one-shot generation
  that accurately corresponds to the users intent exceedingly challenging. In
  addition, to edit a real image using these state-of-the-art tools, one must
  first invert the image into the pre-trained models domain - adding another
  factor affecting the edit quality, as well as latency. In this exploratory
  report, we propose LEDITS - a combined lightweight approach for real-image
  editing, incorporating the Edit Friendly DDPM inversion technique with Semantic
  Guidance, thus extending Semantic Guidance to real image editing, while
  harnessing the editing capabilities of DDPM inversion as well. This approach
  achieves versatile edits, both subtle and extensive as well as alterations in
  composition and style, while requiring no optimization nor extensions to the
  architecture.
paper_ai_summary: LEDITS combines Edit Friendly DDPM inversion and Semantic Guidance to enable versatile and efficient real-image editing using text prompts.
paper_ai_keywords: diffusion models image-generation text-guided editing DDPM inversion Semantic Guidance real-image editing composition style