Generating multimodal image edits for a digital image

In a digital medium environment for editing digital images, a method of providing a plurality of differently edited digital images, the method comprising:

• receiving a digital image from a client device;
• generating a feature vector representing the digital image, wherein generating the feature vector includes feeding the digital image into a convolutional neural network, wherein each value of the feature vector represents a feature of the digital image;
• determining at least one latent variable from noise data;
• determining a plurality of potential image edits based on the feature vector of the digital image and the at least one latent variable by feeding the feature vector and the at least one latent variable into a conditional variational autoencoder;
• identifying a subset of image edits from the plurality of potential image edits by clustering the plurality of potential image edits;
• and
• providing a set of differently edited versions of the digital image, each edited version of the digital image comprising an image edit of the subset of image edits applied to the digital image.

A non-transitory computer readable medium comprising instructions that, when executed by at least one processor, cause a computer system to:

• receive a digital image from a client device;
• generate a feature vector representing the digital image, wherein generating the feature vector includes feeding the digital image into a convolutional neural network, wherein each value of the feature vector represents a feature of the digital image;
• determine at least one latent variable from noise data;
• determine a plurality of potential image edits based on the feature vector of the digital image and the at least one latent variable by feeding the feature vector and the at least one latent variable into a conditional variational autoencoder;
• identify a subset of image edits from the plurality of potential image edits by clustering the plurality of potential image edits;
• and
• provide a set of differently edited versions of the digital image, each edited version of the digital image comprising an image edit of the subset of image edits applied to the digital image.