Stablediffusion-reference-only Alternatives
Similar projects and alternatives to stablediffusion-reference-only
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stable-diffusion-reference-only
img2img version of stable diffusion. Anime Character Remix. Line Art Automatic Coloring. Style Transfer.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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stablediffusion-reference-only reviews and mentions
Posts with mentions or reviews of stablediffusion-reference-only.
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and similar projects. The last one was on 2023-11-08.
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Stable Diffusion Reference Only: : Image Prompt and Blueprint Jointly Guided Multi-Condition Diffusion Model for Secondary Painting
Stable Diffusion and ControlNet have achieved excellent results in the field of image generation and synthesis. However, due to the granularity and method of its control, the efficiency improvement is limited for professional artistic creations such as comics and animation production whose main work is secondary painting. In the current workflow, fixing characters and image styles often need lengthy text prompts, and even requires further training through TextualInversion, DreamBooth or other methods, which is very complicated and expensive for painters. Therefore, we present a new method in this paper, Stable Diffusion Reference Only, a images-to-image self-supervised model that uses only two types of conditional images for precise control generation to accelerate secondary painting. The first type of conditional image serves as an image prompt, supplying the necessary conceptual and color information for generation. The second type is blueprint image, which controls the visual structure of the generated image. It is natively embedded into the original UNet, eliminating the need for ControlNet. We released all the code for the module and pipeline, and trained a controllable character line art coloring model at https://github.com/aihao2000/stablediffusion-reference-only, that achieved state-of-the-art results in this field. This verifies the effectiveness of the structure and greatly improves the production efficiency of animations, comics, and fanworks.
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