# Identifying tourist destinations from movie scenes using Deep Learning

arXiv: https://arxiv.org/abs/2312.00098 · HTML: https://mlsanity.com/paper/2312.00098/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 7 references that are in the map.
- First posted on arXiv 30 Nov 2023.

## Builds on (most cited first, 1 of 1)

- [Learning Patterns of Tourist Movement and Photography from Geotagged Photos at Archaeological Heritage Sites in Cuzco, Peru](https://mlsanity.com/paper/2006.16424/) (2020)

## Abstract (arXiv)

Movies wield significant influence in our lives, playing a pivotal role in the tourism industry of any country. The inclusion of picturesque landscapes, waterfalls, and mountains as backdrops in films serves to enhance the allure of specific scenarios. Recognizing the impact of movies on tourism, this paper introduces a method for identifying tourist destinations featured in films. We propose the development of a deep learning model capable of recognizing these locations during movie viewing. The model is trained on a dataset comprising major tourism destinations worldwide. Through this research, the goal is to enable viewers to identify the real-world locations depicted in movie scenes, offering a novel way to connect cinema with global travel experiences.