  Progress in image captioning is gradually getting complex as researchers try
to generalized the model and define the representation between visual features
and natural language processing. This work tried to define such kind of
relationship in the form of representation called Tensor Product Representation
(TPR) which generalized the scheme of language modeling and structuring the
linguistic attributes (related to grammar and parts of speech of language)
which will provide a much better structure and grammatically correct sentence.
TPR enables better and unique representation and structuring of the feature
space and will enable better sentence composition from these representations. A
large part of the different ways of defining and improving these TPR are
discussed and their performance with respect to the traditional procedures and
feature representations are evaluated for image captioning application. The new
models achieved considerable improvement than the corresponding previous
architectures.
