The Wan 2.1 I2V 14B 480P model is part of the Wan2.1 suite of open video foundation models, representing a significant advancement in image-to-video generation capabilities. This model specifically focuses on generating 480P videos with an emphasis on fast generation while maintaining high quality output.
Architecture and Technology
The model is built on the diffusion transformer paradigm, incorporating several innovative architectural elements. At its core, it utilizes a T5 Encoder for processing multilingual text input, combined with cross-attention mechanisms in each transformer block. The architecture features a dimension of 5120, with input and output dimensions of 16, a feedforward dimension of 13824, and includes 40 attention heads across 40 layers.
A key technological innovation is the implementation of Wan-VAE, a novel 3D causal Variational Autoencoder that can encode and decode 1080P videos of unlimited length while preserving temporal information. The model processes time embeddings through an MLP with a Linear layer and SiLU layer to predict modulation parameters.
Training and Performance
The model was trained on a large-scale, carefully curated dataset that underwent a four-step cleaning process focusing on fundamental dimensions, visual quality, and motion quality. This rigorous data preparation has contributed to the model's superior performance.
In performance evaluations, Wan2.1 I2V 14B 480P has demonstrated superior results compared to both open-source and closed-source alternatives. The model's computational efficiency has been extensively tested across different GPU configurations:
Model Family and Variants
The Wan2.1 family includes several variants, each optimized for specific use cases:
- I2V-14B-480P: The focus model of this article, optimized for 480P image-to-video generation
- I2V-14B-720P: A higher resolution variant for image-to-video generation
- T2V-14B: Supports both 480P and 720P resolutions for text-to-video generation
- T2V-1.3B: A lighter model supporting 480P resolution with less stable 720P capability
A distinguishing feature across all variants is their ability to generate visual text in both Chinese and English, making them versatile tools for multilingual content creation.
References and Further Reading
- Hugging Face Model Repository - Primary model repository and documentation
- GitHub Repository - Source code and implementation details
- ModelScope Repository - Alternative model hosting and documentation
- Project Website - Official project website and updates
The model is released under the Apache 2.0 license, enabling broad use and modification by the research community while maintaining appropriate attribution requirements.
