Face Image Retrieval

Face Image Retrieval#

Image retrieval is the process of finding images relevant to a given query. Traditionally, this is done using metadata such as tags or descriptions. A more advanced approach is to retrieve images based on their visual content, allowing searches to be driven by characteristics like color, texture, and shape.

In this project, you will develop a content-based image retrieval system with PyTorch. You will focus on the case where the query is a list of facial attributes (male, blond, smiling, …), and the goal is to retrieve images of people that match these attributes. You will build a multimodal retrieval system that can learn a similarity metric between images and attributes, and then use this metric to retrieve images that match the query.

Difficulty

Suggested Tutorials

Moderate

Convolutional Networks, Feature Extraction, Weak Supervision

Retrieval


Grading

The project will be graded based on the following criteria. Points for each activity are awarded based on quality and completeness (partial credit possible).

Activity

Points (max)

Build a baseline image retrieval system

9

Properly evaluate its performance (precision, recall)

3

Transfer learning (fine-tuning)

3

Deployment (model made usable)

2

Presentation (clarity & demo)

3

Total

0-20