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HunyuanVideo Keyframe Control Lora is an adapter for HunyuanVideo T2V model for keyframe-based video generation. Our architecture builds upon existing models, introducing key enhancements to optimize keyframe-based video generation:
We modify the input patch embedding projection layer to effectively incorporate keyframe information. By adjusting the convolutional input parameters, we enable the model to process image inputs within the Diffusion Transformer (DiT) framework.
We apply Low-Rank Adaptation (LoRA) across all linear layers and the convolutional input layer. This approach facilitates efficient fine-tuning by introducing low-rank matrices that approximate the weight updates, thereby preserving the base model's foundational capabilities while reducing the number of trainable parameters.
The model is conditioned on user-defined keyframes, allowing precise control over the generated video's start and end frames. This conditioning ensures that the generated content aligns seamlessly with the specified keyframes, enhancing the coherence and narrative flow of the video.
The text was updated successfully, but these errors were encountered:
https://github.com/dashtoon/hunyuan-video-keyframe-control-lora
HunyuanVideo Keyframe Control Lora is an adapter for HunyuanVideo T2V model for keyframe-based video generation. Our architecture builds upon existing models, introducing key enhancements to optimize keyframe-based video generation:
We modify the input patch embedding projection layer to effectively incorporate keyframe information. By adjusting the convolutional input parameters, we enable the model to process image inputs within the Diffusion Transformer (DiT) framework.
We apply Low-Rank Adaptation (LoRA) across all linear layers and the convolutional input layer. This approach facilitates efficient fine-tuning by introducing low-rank matrices that approximate the weight updates, thereby preserving the base model's foundational capabilities while reducing the number of trainable parameters.
The model is conditioned on user-defined keyframes, allowing precise control over the generated video's start and end frames. This conditioning ensures that the generated content aligns seamlessly with the specified keyframes, enhancing the coherence and narrative flow of the video.
The text was updated successfully, but these errors were encountered: