Recognizing Families through Images with Pretrained Encoder (FG 2020)

Kinship retrieval sample results (Rank 10). For each query (row) one or more faces of the probe returned the corresponding samples of gallery as top 10. x (red) depicts false predictions. True predictions display the relationship type ( green): P for parent; C for child; S for sibling.

Abstract

Kinship verification and kinship retrieval are emerging tasks in computer vision. Kinship verification aims at determining whether two facial images are from related people or not, while kinship retrieval is the task of retrieving possible related facial images to a person from a gallery of images. They introduce unique challenges because of the hidden relations and features that carry inherent characteristics between the facial images. We employ 3 methods, FaceNet, Siamese VGGFace, and a combination of FaceNet and VGG-Face models as feature extractors, to achieve the 9th standing for kinship verification and the 5th standing for kinship retrieval in the Recognizing Family in The Wild 2020 competition. We then further experimented using StyleGAN2 as another encoder, with no improvement in the result.

Publication
In 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition

We employ 3 methods, FaceNet, Siamese VGGFace, and a combination of FaceNet and VGG-Face models as feature extractors, to achieve the 9th standing for kinship verification and the 5th standing for kinship retrieval in the Recognizing Family in The Wild 2020 competition.

Tuan-Duy H. Nguyen
Tuan-Duy H. Nguyen
ML + Data Engineer/Researcher