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Video captioning is the process of describing the content of a sequence ofimages capturing its semantic relationships and meanings. Dealing with thistask with a single image is arduous, not to mention how difficult it is for avideo (or images sequence). The amount and relevance of the applications ofvideo captioning are vast, mainly to deal with a significant amount of videorecordings in video surveillance, or assisting people visually impaired, tomention a few. To analyze where the efforts of our community to solve the videocaptioning task are, as well as what route could be better to follow, thismanuscript presents an extensive review of more than 105 papers for the periodof 2016 to 2021. As a result, the most-used datasets and metrics areidentified. Also, the main approaches used and the best ones. We compute a setof rankings based on several performance metrics to obtain, according to itsperformance, the best method with the best result on the video captioning task.Finally, some insights are concluded about which could be the next steps oropportunity areas to improve dealing with this complex task.

Video Captioning: a comparative review of where we are and which could be the route