Learning and propagating visual attributes

A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to perform the steps of:

• generating a first directed acyclic graph (DAG) by connecting spatially adjacent points included in a set of unstructured points via directed edges along a first direction;
• applying a first set of neural network layers to one or more images associated with the set of unstructured points to generate (i) a set of features for the set of unstructured points and (ii) a set of pairwise affinities between the spatially adjacent points connected by the directed edges;
• and
• generating a set of labels for the set of unstructured points by propagating the set of features across the first DAG based on the set of pairwise affinities.

A system, comprising:

• a memory that stores instructions, and
• a processor that is coupled to the memory and, when executing the instructions, is configured to:
• generate a first directed acyclic graph (DAG) by connecting spatially adjacent points included in a set of spatially distributed points via directed edges along a first direction;
• apply a first set of neural network layers to one or more images associated with the set of spatially distributed points to generate (i) a set of features for the set of spatially distributed points and (ii) a set of pairwise affinities between the spatially adjacent points connected by the directed edges;
• and
• generate a set of labels for the set of spatially distributed points by propagating the set of features across the first DAG based on the set of pairwise affinities.