Motion customization via shared attention

A method for generating image content, the method comprising:

• processing, using a first machine learning model, a reference image and a reference video including inverted noise to generate first features;
• processing, using a second machine learning model, the reference image and Gaussian noise to generate second features;
• processing, using one or more shared attention layers, the first features from the first machine learning model and the second features from the second machine learning model to generate shared attention features;
• and
• processing, using the second machine learning model, the shared attention features to generate an output video.

A non-transitory computer-readable medium is provided that has stored thereon instructions that, when executed by one or more processors, cause the one or more processors to:

• process, using a first machine learning model, a reference image and a reference video including inverted noise to generate first features;
• process, using a second machine learning model, the reference image and Gaussian noise to generate second features;
• process, using one or more shared attention layers, the first features from the first machine learning model and the second features from the second machine learning model to generate shared attention features;
• and
• process, using the second machine learning model, the shared attention features to generate an output video.