https://github.com/gombru/LocSens

Code of Location Sensitive Image Retrieval and Tagging, ECCV 2020 by Raul Gomez, Jaume Gibert, Lluis Gomez and Dimosthenis Karatzas
https://github.com/gombru/LocSens

image location retrieval sensitive tagging

Last synced: about 1 year ago
JSON representation

Code of Location Sensitive Image Retrieval and Tagging, ECCV 2020 by Raul Gomez, Jaume Gibert, Lluis Gomez and Dimosthenis Karatzas

• Host: GitHub
• URL: https://github.com/gombru/LocSens
• Owner: gombru
• Created: 2020-07-03T10:06:39.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2020-07-08T11:09:12.000Z (almost 6 years ago)
• Last Synced: 2024-08-04T03:10:59.463Z (almost 2 years ago)
• Topics: image, location, retrieval, sensitive, tagging
• Language: Python
• Homepage: https://gombru.github.io/2020/06/03/LocSens/
• Size: 7.43 MB
• Stars: 2
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# Code of Location Sensitive Image Retrieval and Tagging

**ECCV 2020**  

**Raul Gomez, Jaume Gibert, Lluis Gomez and Dimosthenis Karatzas**    

[Paper](https://arxiv.org/abs/2007.03375)  

[Blog Post](https://gombru.github.io/2020/06/03/LocSens/)

**This code needs intense cleaning and simplification that will be done as soon as possible**

## Results Examples

LocSens is able to retrieve images related to a query word and near to a given location:  

![](results/retrieval_results.png)

LocSens is able to tag images exploiting both visual and location information of an image, outperforming location agnostic tagging methods:  

![](results/tagging_results.png)

## Code explanation

Here we explain roughly how this first version of the code works. Each script includes a short explanation of what it does.

### dataset_code

Contains the code to generate the hashtag vocabulary, the splits and the query sets. It works over the YFCC100M dataset, which is available [here](https://multimediacommons.wordpress.com/yfcc100m-core-dataset/).

### splits

Contains the exact splits we used in our paper.

### MCC, MLC, HER

Contain the code to train this models as explained in the paper chapter "Learning with Hashtag Supervision." 

### LocSens

Contains the code to train LocSens.

### evaluation

Contains the code to evaluate both the location agnostic models and LocSens. The code the compute the embeddings used in this evaluations scripts is located in each of the models folders.