InstantID: Personalized Image Synthesis Model

Written By: kinza.sabir
Last Updated On: January 23, 2024

InstantID: Transforming a single personalized image into multiple styles within seconds. The researchers from InstantX Team have presented this amazing and creative model. The model takes a single image and text description as an input and generates customized images with various poses or styles from a single reference image while maintaining high fidelity within seconds.

InstantID Workflow — Workflow of InstantID

Text-to-image technique for image synthesis has evolved drastically over the time but these models require a large storage space, a long time for fine-tuning or multiple reference images. On the other hand, the methods that rely on ID embedding have their own set of challenges as they struggle to accurately maintain and capture fine details of the generated image.

To cater to all these challenges, the researchers presented a powerful solution that is InstantID. It has the ability to generate customized images using a diffusion model. It is extremely adaptable because of its plug-and-play module to generate personalized images in different styles using one facial image. The output generated by this model ensures a high level of detail and accuracy to look close to the original image.

InstantID has the ability to plug-and-play with other models. In pre-trained models it helps to keep the identity intact without using extra resources. Like original Stable Diffusion Model, InstantID also allows good control while editing text which helps to easily integrate ID into numerous styles. InstantID is extremely efficient and it is very useful for different real-world applications by combining different styles in pictures, creating new things and mixing different identities.

Technicalities of InstantID

With the help of only one reference ID image, InstantID instantly creates multiple customized images with different styles and poses of high quality. It consists of three important components;

An ID embedding that stores strong information of a person’s face.
An Image Adapter (customized module) that helps to use input image as guide.
An IdentityNet that captures all the specific details of face in a reference image and control how things are arranged in the generated image

IdentityNet pay extra attention to the meaning and important details while least focusing on the arrangement and locations of the elements.

InstantID is extremely versatile and effective which would be helpful in numerous creative and practical situations such as augmented and virtual reality, variety of digital characters, customized Avatar creation etc. The research is available on Arxiv and code is available on GitHub.

Wrap Up!

From extensive experimentation, the qualitative and quantitative analysis showed that the plug-and-play modules of InstantID helps to create customized images of various styles making the new images look very close to the original images.

According to my opinion, the latest model PhotoMaker, which is also a personlized text-to-image generation model works best because of it additional features compared to InstantID. PhotoMaker has the ability to transform age or gender according to user requirements and brings person from artworks or some old photos into reality. Due to these features it is more effective and efficient in comparison to InstantID.