  Recent advancements in deep learning have created many opportunities to solve
real-world problems that remained unsolved for more than a decade. Automatic
caption generation is a major research field, and the research community has
done a lot of work on it in most common languages like English. Urdu is the
national language of Pakistan and also much spoken and understood in the
sub-continent region of Pakistan-India, and yet no work has been done for Urdu
language caption generation. Our research aims to fill this gap by developing
an attention-based deep learning model using techniques of sequence modeling
specialized for the Urdu language. We have prepared a dataset in the Urdu
language by translating a subset of the "Flickr8k" dataset containing 700 'man'
images. We evaluate our proposed technique on this dataset and show that it can
achieve a BLEU score of 0.83 in the Urdu language. We improve on the previous
state-of-the-art by using better CNN architectures and optimization techniques.
Furthermore, we provide a discussion on how the generated captions can be made
correct grammar-wise.
