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5 repository-uri

Awesome GitHub RepositoriesIdentity Adapters

Specialized adapters for diffusion models that inject subject-specific identity information into the generation process.

Distinct from Diffusion Models: Diffusion Models is the base architecture; this focuses on the adapter mechanism for identity injection.

Explore 5 awesome GitHub repositories matching artificial intelligence & ml · Identity Adapters. Refine with filters or upvote what's useful.

Awesome Identity Adapters GitHub Repositories

Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
  • guoyww/animatediffAvatar guoyww

    guoyww/AnimateDiff

    12,144Vezi pe GitHub↗

    AnimateDiff is a latent diffusion video generator and text-to-video diffusion framework. It converts existing text-to-image diffusion models into animation generators by applying specialized motion modules, allowing for the creation of video sequences without modifying the original base model. The project provides an image-to-video animation framework that uses sparse RGB images, sketches, or structural keyframe constraints to guide generation. It further distinguishes itself with a motion adapter system that injects cinematic camera movements, such as zooming, panning, and tilting, into anim

    Ships lightweight layers that inject cinematic camera movements like zooming and panning into animations.

    Python
    Vezi pe GitHub↗12,144
  • instantx-research/instantidAvatar instantX-research

    instantX-research/InstantID

    11,955Vezi pe GitHub↗

    InstantID is a diffusion-based identity preservation framework designed for zero-shot image generation. It allows for the synthesis of images featuring a specific person's facial identity using a single reference photo without requiring additional model training or fine-tuning. The project distinguishes itself through the use of consistency model distillation to accelerate inference, reducing the number of steps needed to produce high-quality results. It combines identity-preserving feature extraction with multi-modal prompt integration to merge visual embeddings from a reference image with t

    Employs identity adapters within a diffusion framework to maintain facial consistency from a single reference photo.

    Python
    Vezi pe GitHub↗11,955
  • tencentarc/photomakerAvatar TencentARC

    TencentARC/PhotoMaker

    10,122Vezi pe GitHub↗

    PhotoMaker is a diffusion-based identity generator designed for person-specific image synthesis. It creates high-fidelity photos and avatars of specific individuals using stacked embeddings, which allows for the generation of consistent human identities without the need for custom model training or fine-tuning. The system utilizes zero-shot identity synthesis and identity adapters to maintain recognizable facial features across various visual contexts. It supports artistic style transfer by combining identity information with specialized model weights and integrates external control framework

    Provides a framework for injecting specific person-identity information into base diffusion models via embedding manipulation.

    Jupyter Notebook
    Vezi pe GitHub↗10,122
  • lightricks/comfyui-ltxvideoAvatar Lightricks

    Lightricks/ComfyUI-LTXVideo

    3,840Vezi pe GitHub↗

    ComfyUI-LTXVideo is a generative framework and ComfyUI custom node extension for synthesizing high-fidelity video. It utilizes a latent diffusion and transformer-based system to create cinematic clips from text, image, and audio inputs, providing a modular interface for precise control over subject behavior and temporal consistency. The tool distinguishes itself with production-grade capabilities, including the generation of High Dynamic Range video in linear formats such as ARRI LogC3. It supports multimodal synchronization for audio-driven animation and lip-syncing, and allows for the creat

    Ships identity adapters to inject subject-specific information into the video generation process.

    Pythoncomfyuidiffusion-modelsdit
    Vezi pe GitHub↗3,840
  • nunchaku-ai/comfyui-nunchakuAvatar nunchaku-ai

    nunchaku-ai/ComfyUI-nunchaku

    2,901Vezi pe GitHub↗

    ComfyUI-nunchaku is a 4-bit diffusion inference engine and a set of nodes for running low-precision quantized diffusion models within ComfyUI visual workflows. It provides a backend that reduces memory overhead and increases generation speed for transformer models. The project includes specialized tools for identity-preserving generation and an image-to-image guidance toolkit that uses depth maps and reference images. It also features a multimodal visual question answering implementation and a utility for merging multiple quantized model files into single unified files. The engine covers a b

    Integrates specialized identity adapters into diffusion models to maintain consistent person-specific features.

    Pythoncomfyuidiffusionflux
    Vezi pe GitHub↗2,901
  1. Home
  2. Artificial Intelligence & ML
  3. Generative AI Resources
  4. Diffusion & Visual Synthesis Models
  5. Generative AI Models
  6. Diffusion Models
  7. Identity Adapters

Explorează sub-etichetele

  • Motion AdaptersLightweight layers that inject specific movements into generative models. **Distinct from Identity Adapters:** Focuses on injecting cinematic camera motion rather than subject-specific identity information.