A computer-implemented method, the method comprising: obtaining, by one or more computing devices, an image of a face; obtaining, by the one or more computing devices, an embedding supplied by a machine-learned image recognition model, the embedding supplied by the machine-learned image recognition model in response to receipt of the image of the face by the image recognition model, wherein the embedding comprises a feature vector for the image of the face, for input into a machine-learned translational model; inputting, by the one or more computing devices, the embedding into the machine-learned translation model, the machine-learned translation model having been trained on a set of training data that includes a plurality of example embeddings labeled with a plurality of example facial modeling parameter values usable by a face modeler to generate a model of a face, wherein the example embeddings are obtained by inputting example faces into the machine-learned image recognition model, said example faces being generated by the face modeler using the respective example facial modeling parameter values; receiving, by the one or more computing devices, a plurality of facial modeling parameter values as an output of the translation model, the plurality of facial modeling parameter values descriptive of a plurality of facial attributes of the face included in the image obtained by the one or more computing devices; inputting, by the one or more computing devices, the plurality of facial modeling parameter values into said face modeler; and receiving, by the one or more computing devices, a model of the face as an output of the face modeler. obtaining, by one or more computing devices, an image of a face; obtaining, by the one or more computing devices, an embedding supplied by a machine-learned image recognition model, the embedding supplied by the machine-learned image recognition model in response to receipt of the image of the face by the image recognition model, wherein the embedding comprises a feature vector for the image of the face, for input into a machine-learned translational model; inputting, by the one or more computing devices, the embedding into the machine-learned translation model, the machine-learned translation model having been trained on a set of training data that includes a plurality of example embeddings labeled with a plurality of example facial modeling parameter values usable by a face modeler to generate a model of a face, wherein the example embeddings are obtained by inputting example faces into the machine-learned image recognition model, said example faces being generated by the face modeler using the respective example facial modeling parameter values; receiving, by the one or more computing devices, a plurality of facial modeling parameter values as an output of the translation model, the plurality of facial modeling parameter values descriptive of a plurality of facial attributes of the face included in the image obtained by the one or more computing devices; inputting, by the one or more computing devices, the plurality of facial modeling parameter values into said face modeler; and receiving, by the one or more computing devices, a model of the face as an output of the face modeler.