ID-Preserving generation research paper using a single image
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InstantID offers a zero-shot, single-image method for identity-preserving image generation, targeting researchers and artists. It enables users to generate diverse images while maintaining a specific identity, offering flexibility across various downstream tasks.
How It Works
InstantID leverages a novel tuning-free approach by integrating an Identity Encoder with Stable Diffusion. It uses a pre-trained ControlNet (IdentityNet) to capture identity information from a single input image and an IP-Adapter to inject this identity into the generation process. This combination allows for high-fidelity identity preservation without requiring model fine-tuning, offering a balance between identity retention and prompt controllability.
Quick Start & Requirements
pip install opencv-python transformers accelerate insightface diffusers
antelopev2
face encoder model (manual download required).Highlighted Details
diffusers
library.Maintenance & Community
haofanwang.ai@gmail.com
or wangqixun.ai@gmail.com
.Licensing & Compatibility
antelopev2
) and released checkpoints are for non-commercial research purposes only, as per insightface's license.Limitations & Caveats
The project currently does not support multi-person generation, processing only the largest detected face. The licensing for the face encoder and checkpoints restricts their use to research purposes, which may impact commercial applications.
1 year ago
Inactive