Computer-implemented segmentation techniques are disclosed for identifying features in an image based on text tags. The method comprises: converting a tag 118 into a vector representation 202, the tag defining a semantic class 120 to be located in a digital image 106; generating an attention map 210 by an embedding neural network 208 based on the digital image and the vector representation, the attention map defining a location in the digital image that corresponds to the semantic class, where the embedding neural network has been trained using image-level tags of respective semantic classes; refining 212 the location of the semantic class in the attention map by a refinement neural network 214 , the refinement neural network trained using localized tags of respective semantic classes; and indicating the refined location of the semantic class in the digital image using the refined attention map 216. The method thus makes use of tags for similar items in a machine learning environment in order to provide more examples for training.
Semantic class localization digital environment