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Concept Sliders is a LoRA adapter for diffusion models such as Stable Diffusion that allows users to have fine-grained control over specific concepts during image generation . Unlike traditional methods that rely on cue words to generate images, Concept Sliders introduces adjustable "sliders" that allow users to adjust the intensity of certain specific attributes (such as eye size, lighting intensity, style, etc.) while keeping the overall structure of the image unchanged, thereby achieving higher-precision image generation and editing without having to repeatedly modify the cue words.
- Concept Sliders: Create sliders for specific concepts in the diffusion model, allowing users to control specific features of image generation or editing, such as age, gender, eye size, etc., by adjusting the slider's value.
- Support for multiple diffusion models: Supports diffusion model training for SD1.x and SD2.x versions, and also includes extensions for the SD-XL version.
- The project supports experimental slider training for the FLUX-1 model, which, although different from the SDXL architecture, can be used to try out FLUX-based sliders.
- Text Slider: A slider based on text description. By inputting a description such as "I want to make people look happier", a corresponding slider is generated.
- Image Sliders: Sliders can be trained to implement image editing based on a set of images (such as before and after image pairs).
- The project integrates ControlNet functions, allowing community users to further enhance the control effect of the slider and expand its application scenarios through this technology.
Key Features of Concept Sliders
Fine-tune the concept in the image
- Fine-tune the diffusion model through the LoRA adapter
to create sliders for precise control of specific image features. For example, control age, gender, expression, etc.
- Users can control certain elements in the image by simply sliding and adjusting parameters to achieve control over specific features in the generated or edited image. For example, you can make a person's eyes bigger or smaller, or adjust the light intensity in the picture. This control is continuous, and you can fine-tune it according to your needs until you are satisfied.
Text concept slider
- Users can generate sliders by describing text. For example, if you enter "I want people to look happier", the model will generate a slider for adjusting the degree of "happiness".
- Provides GPT-4 integrated function to generate sliders, making it easier to create sliders.
- When you generate images from prompts, you often want to make more detailed adjustments to certain attributes, such as the transition between "young" and "old". Text concept sliders allow you to train the model to remember these concepts by inputting simple text descriptions, and then use sliders to control the strength of this concept. For example, you can make the person in the image gradually age as the slider moves, without changing other attributes.
By using a small set of textual descriptions of the attributes to control, Concept Sliders can be trained to allow finegrained control of generated images during inference. By scaling the slider factor, users can control the strength of the edit.
We show how several attributes of an image can be controlled using different sliders. We note that due to the low-rank formulation, the parameters are light weight, easy to share, and plug.
We demonstrate weather sliders for “delightful”, “dark”, “tropical”, and “winter”. For delightful, we notice that the model sometimes make the weather bright or adds festive decorations. For tropical, it adds tropical plants and trees. Finally, for winter, it adds snow.
We demonstrate style sliders for “pixar”, “realistic details”, “clay”, and “sculpture”.
Visual Concept Slider
- Supports training sliders based on a set of images (e.g., before and after image pairs) to achieve precise control of specific visual features (e.g., eye size, facial features, etc.).
- It can be used to make detailed edits to the properties of an image, such as enlarging eyes, changing facial expressions, etc.
- Some visual elements may be difficult to describe in words, such as subtle changes in facial expressions or different lighting effects. For these concepts that are difficult to describe in words, Concept Sliders supports training sliders through paired images. You can select several pictures with contrasting effects to train the model to recognize these details, and then adjust these visual elements through sliders.
Sliders can be created for concepts that can not be described in words. These sliders are created by artists by using 6-8 pairs of images.
Stylespace latents can be transferred from styleGAN to Stable Diffusion XL.
Fix image defects
When generating images, the model sometimes has some common problems, such as unnatural hand shapes, blurry objects, or distorted lines. Concept Sliders provides a "healing slider" that can help fix these problems. By adjusting the slider, you can make the model generate clearer, more realistic images with less distortion or blurriness.
The repair slider enables the model to generate images that are more realistic and undistorted. The parameters under the control of this slider help the model correct some of the flaws in their generated outputs like distorted humans and pets in (a, b), unnatural objects in (b, c, d), and blurry natural images in (b,c).
We demonstrate the effect of our “repair” slider on fine details: it improves the rendering of densely arranged objects, it straightens architectural lines, and it avoids blurring and distortions at the edges of complex shapes.
We demonstrate a slider for fixing hands in stable diffusion. We find a direction to steer hands to be more realistic and away from “poorly drawn hands”.
Image Editing
Real-life image editing with sliders. Null Inversion technology allows you to modify specific areas of an image using sliders without text cues.
This greatly simplifies the image editing process and is suitable for processing various pictures and visual tasks.
To combine multiple sliders
If you want to control multiple image elements at the same time, Concept Sliders allows you to combine multiple sliders. For example, you can adjust multiple details such as lighting effects, weather, style, etc. at the same time, which can produce more complex and layered images. For example, you can adjust the weather slider to "Winter" and the style slider to "Pixar Style" at the same time to achieve a specific effect.
We show blending “cooked” and “fine dining” food sliders to traverse this 2D concept space. It is interesting how the model makes portion sizes small for “fine dining”.
We qualitatively show the effects of composing multiple sliders progressively up to 50 sliders at a time. We use far greater than 77 tokens (the current context limit of SDXL) to create these 50 sliders. This showcases the power of our method that allows control beyond what is possible through prompt-based methods alone.
Avoid interfering with other properties
Sometimes, when you adjust one attribute (such as changing a character's age), other unrelated attributes (such as the character's race) will also change, causing the image to be distorted. Concept Sliders introduces a method to keep certain attributes unchanged, such as keeping the character's race and gender unchanged when you change the age, thus avoiding the distorted image effect.
What can you do with Concept Sliders?
- More precise creation: If you are creating a work of art, you can first generate a base image, and then gradually adjust the details in the image through the slider until it is exactly what you want, without having to constantly modify the prompt words and regenerate them.
- Repair problem images: If your generated image has problems such as unnatural fingers and crooked building lines, you can use the repair slider to improve these details and improve the image quality.
- Multiple style controls: You can adjust multiple sliders at the same time to generate mixed-style images, such as combining "cartoon style" and "retro style", or making the weather in the picture gradually transition from "sunny" to "winter".
Technical Highlights of Concept Sliders
Lightweight and fast
LoRA technology makes model adjustments lightweight. There is no need to retrain the entire model. You only need to modify a small number of parameters to quickly achieve the desired effect.
High-precision control
Concept Sliders allow you to make continuous, precise adjustments to specific details in your image without having to regenerate or enter complex prompts.
Adjust multiple attributes simultaneously
You can use multiple sliders to control different image attributes at the same time to achieve complex combination effects.
Project Website | Arxiv Preprint | Trained Sliders | Colab Demo | Huggingface Demo
- Author:KCGOD
- URL:https://kcgod.com/Concept-Sliders
- Copyright:All articles in this blog, except for special statements, adopt BY-NC-SA agreement. Please indicate the source!
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