# hvision-nku/storydiffusion **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/hvision-nku-storydiffusion).** 6,430 stars · 642 forks · Jupyter Notebook · Apache-2.0 ## Links - GitHub: https://github.com/HVision-NKU/StoryDiffusion - awesome-repositories: https://awesome-repositories.com/repository/hvision-nku-storydiffusion.md ## Description StoryDiffusion is a generative AI system designed for consistent character image and video generation. It utilizes a pluggable cross-attention module to inject shared character representations into pretrained diffusion models, allowing for visual identity stability across multiple images and scenes without retraining the base model. The project features a video generation pipeline that produces temporally coherent sequences from text prompts or condition images. It employs a latent space motion interpolator to predict intermediate frames and semantic motion, enabling long-range video generation and larger motion transitions by operating within a compressed variational autoencoder space. The system includes capabilities for AI comic creation and a text-to-video pipeline. To support hardware accessibility, it implements precision-reduced model serving and low-memory inference to run the full generation pipeline on consumer GPUs. An interactive demo interface is provided via a local web dashboard for content creation. ## Tags ### Artificial Intelligence & ML - [Text-to-Video Generators](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-ai-pipelines/text-to-video-generators.md) — Combines consistent character generation with motion prediction to synthesize high-quality, temporally coherent videos from text prompts. ([source](https://cdn.jsdelivr.net/gh/hvision-nku/storydiffusion@main/README.md)) - [Attention Layer Injectors](https://awesome-repositories.com/f/artificial-intelligence-ml/attention-mechanisms/attention-layer-injectors.md) — Provides a mechanism for injecting external control signals into the attention layers of a diffusion model to enforce identity. - [Latent Motion Prediction](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-ai-models/latent-space-generative-models/motion-latent-modeling/latent-motion-prediction.md) — Forecasts intermediate frames between condition images by operating in a compressed latent space. - [Cross-Frame Attention Layers](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-ai-pipelines/text-to-video-generators/cross-attention-conditioning/cross-frame-attention-layers.md) — Utilizes specialized attention layers to maintain visual character consistency across sequential frames. - [Video Diffusion Models](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-models/latent-diffusion-models/video-diffusion-models.md) — Uses a latent diffusion model to produce temporally coherent video sequences from text prompts. - [Noise-to-Image Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-image-models/noise-to-image-generation.md) — Generates high-quality visuals by reversing the noise process via iterative denoising. - [Image-Conditioned Video Generators](https://awesome-repositories.com/f/artificial-intelligence-ml/image-generation-models/conditional-image-generation/image-conditioned-video-generators.md) — Creates videos by analyzing provided keyframe images and predicting the motion between them. ([source](https://cdn.jsdelivr.net/gh/hvision-nku/storydiffusion@main/README.md)) - [Image-to-Video Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/video-generation/image-to-video-generation.md) — Synthesizes motion sequences using keyframe images and text prompts as guidance. - [Long-form Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/video-generation/video-clip-generators/long-form-generation.md) — Produces extended video sequences by predicting motion between a series of condition images in a compressed semantic space. ([source](https://cdn.jsdelivr.net/gh/hvision-nku/storydiffusion@main/README.md)) - [Visual Identity Consistency](https://awesome-repositories.com/f/artificial-intelligence-ml/visual-identity-consistency.md) — Maintains consistent characters and visual identities across multiple generated images. - [Memory-Constrained Inference](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-optimization-and-inference/serving-and-runtime/large-language-model-optimization/memory-constrained-inference.md) — Implements techniques to run large generative models within the memory constraints of consumer GPUs. - [Mixed-Precision Quantization](https://awesome-repositories.com/f/artificial-intelligence-ml/model-optimization/compression-techniques/model-pruning/model-compression-suites/half-precision-compression/mixed-precision-quantization.md) — Reduces GPU memory footprint by converting model weights to lower numerical precision. ### Part of an Awesome List - [Video and Motion Synthesis](https://awesome-repositories.com/f/awesome-lists/ai/video-and-motion-synthesis.md) — Analyzes motion between condition images in a compressed semantic space to enable large video transitions. ([source](https://cdn.jsdelivr.net/gh/hvision-nku/storydiffusion@main/README.md)) ### Graphics & Multimedia - [Latent Frame Interpolators](https://awesome-repositories.com/f/graphics-multimedia/motion-vector-calculation/motion-based-frame-interpolation/latent-frame-interpolators.md) — Generates intermediate video frames by interpolating semantic data within a variational autoencoder. - [AI Comic Generation](https://awesome-repositories.com/f/graphics-multimedia/ai-comic-generation.md) — Generates series of visually consistent images to tell stories through an interactive interface. ### User Interface & Experience - [Generative Character Consistency](https://awesome-repositories.com/f/user-interface-experience/character-encoding-support/chinese-character-support/customizable-character-models/generative-character-consistency.md) — Implements methods to maintain visual continuity of character identities across multiple AI-generated scenes. - [Visual Character Consistency](https://awesome-repositories.com/f/user-interface-experience/character-encoding-support/chinese-character-support/customizable-character-models/generative-character-consistency/visual-character-consistency.md) — Ensures characters remain visually stable across different prompts and scenes using specialized attention. ([source](https://cdn.jsdelivr.net/gh/hvision-nku/storydiffusion@main/README.md)) - [Semantic Motion Interpolations](https://awesome-repositories.com/f/user-interface-experience/coordinate-normalization/normal-interpolation/vector-interpolators/latent-space-interpolations/semantic-motion-interpolations.md) — Predicts intermediate video frames by interpolating semantic representations within a compressed variational autoencoder space. ### DevOps & Infrastructure - [Consumer GPU Optimizations](https://awesome-repositories.com/f/devops-infrastructure/model-serving/consumer-gpu-optimizations.md) — Enables full generation pipelines to run on consumer GPUs by reducing batch size and model precision.