Image Editing

BAGEL is a unified multimodal model that can understand and generate images and text, excelling in tasks like image editing and predicting future frames. Basically the open-source version of GPT-4o.

Marigold can estimate depth, predict surface normals, and decompose images with minimal changes.

Step1X-Edit can perform advanced image editing tasks by processing reference images and user instructions.

PosterMaker can generate high-quality product posters by rendering text accurately and keeping the main subject clear.

Piece it Together can combine different visual components into complete characters or objects. It uses a lightweight flow-matching model called IP-Prior to improve prompt adherence and enable diverse, context-aware generations.

SISO can generate and edit images using just one subject image without any training. It improves image quality, keeps the subject clear, and preserves the background better than other methods.

InfiniteYou can generate high-quality images with FLUX and retain a person’s identity.

Diptych Prompting can generate images of new subjects in specific contexts by treating text-to-image generation as an inpainting task.

MagicColor can automatically colorize multi-instance sketches while keeping colors consistent across objects using reference images.

ImageRAG can find relevant images based on a text prompt to improve image generation. It helps create rare and detailed concepts without needing special training, making it useful for different image models.

KV-Edit can edit images while keeping the background consistent. It allows users to add, remove, or change objects without needing extra training, ensuring high image quality.

Any2AnyTryon can generate high-quality virtual try-on results by transferring clothes onto images as well as reconstructing garments from real-world images.

MIGE can generate images from text prompts and reference images and edit existing images based on instructions.

InstantSwap can swap concepts in images from a reference image while keeping the foreground and background consistent. It uses automated bounding box extraction and cross-attention to make the process more efficient by reducing unnecessary calculations.

MaterialFusion can transfer materials onto objects in images while letting users control how much material is applied.

ControlFace can edit face images with precise control over pose, expression, and lighting. It uses a dual-branch U-Net architecture and is trained on facial videos to ensure high-quality results while keeping the person’s identity intact.

Stable Flow can edit images by adding, removing, or changing objects.

FramePainter can edit images using simple sketches and video diffusion methods. It allows for realistic changes, like altering reflections or transforming objects, while needing less training data and performing well in different situations.

One-Prompt-One-Story can generate consistent images from a single text prompt by combining all prompts into one input for text-to-image models.

Chat2SVG can generate and edit SVG vector graphics from text prompts. It combines Large Language Models and image diffusion models to create detailed SVG templates and allows users to refine them with simple language instructions.