  The use of deep learning techniques has exploded during the last few years,
resulting in a direct contribution to the field of artificial intelligence.
This work aims to be a review of the state-of-the-art in scene recognition with
deep learning models from visual data. Scene recognition is still an emerging
field in computer vision, which has been addressed from a single image and
dynamic image perspective. We first give an overview of available datasets for
image and video scene recognition. Later, we describe ensemble techniques
introduced by research papers in the field. Finally, we give some remarks on
our findings and discuss what we consider challenges in the field and future
lines of research. This paper aims to be a future guide for model selection for
the task of scene recognition.
