Abstract
Deep learning has achieved great successes in solving specific artificial intelligence problems recently.
Substantial progresses are made on Computer Vision (CV) and Natural Language Processing (NLP).
As a connection between the two worlds of vision and language, video captioning is the task of producing a natural-language utterance (usually a sentence) that describes the visual content of a video. The task is naturally decomposed into two sub-tasks.
One is to encode a video via a thorough understanding and learn visual representation. The other is caption generation, which decodes the learned representation into a sequential sentence, word by word.
In this survey, we first formulate the problem of video captioning, then review state-of-the-art methods categorized by their emphasis on vision or language, and followed by a summary of standard datasets and representative approaches.
Finally, we highlight the challenges which are not yet fully understood in this task and present future research directions.
Keywords
- Computer Vision: Language and Vision
- Natural Language Processing: Natural Language Generation
- Machine Learning: Deep Learning
- Computer Vision: Video: Events, Activities and Surveillance
