# The 5th Recognizing Families in the Wild Data Challenge: Predicting Kinship from Faces

arXiv: https://arxiv.org/abs/2111.00598 · HTML: https://mlsanity.com/paper/2111.00598/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 51 references that are in the map.
- First posted on arXiv 31 Oct 2021.

## Builds on (most cited first, 24 of 24)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [A Simple Framework for Contrastive Learning of Visual Representations](https://mlsanity.com/paper/2002.05709/) (2020)
- [Evaluating Large Language Models Trained on Code](https://mlsanity.com/paper/2107.03374/) (2021)
- [Squeeze-and-Excitation Networks](https://mlsanity.com/paper/1709.01507/) (2017)
- [FaceNet: A Unified Embedding for Face Recognition and Clustering](https://mlsanity.com/paper/1503.03832/) (2015)
- [SphereFace: Deep Hypersphere Embedding for Face Recognition](https://mlsanity.com/paper/1704.08063/) (2017)
- [Deep Face Recognition: A Survey](https://mlsanity.com/paper/1804.06655/) (2018)
- [Face Recognition: Too Bias, or Not Too Bias?](https://mlsanity.com/paper/2002.06483/) (2020)
- [Balancing Biases and Preserving Privacy on Balanced Faces in the Wild](https://mlsanity.com/paper/2103.09118/) (2021)
- [Laplace Landmark Localization](https://mlsanity.com/paper/1903.11633/) (2019)
- [Families in the Wild (FIW): Large-Scale Kinship Image Database and Benchmarks](https://mlsanity.com/paper/1604.02182/) (2016)
- [Tri-Subject Kinship Verification: Understanding the Core of A Family](https://mlsanity.com/paper/1501.02555/) (2015)
- [Deep Fusion Siamese Network for Automatic Kinship Verification](https://mlsanity.com/paper/2006.00143/) (2020)
- [KinshipGAN: Synthesizing of Kinship Faces From Family Photos by Regularizing a Deep Face Network](https://mlsanity.com/paper/1806.08600/) (2018)
- [Multi-Prototype Networks for Unconstrained Set-based Face Recognition](https://mlsanity.com/paper/1902.04755/) (2019)
- [Achieving Better Kinship Recognition Through Better Baseline](https://mlsanity.com/paper/2006.11739/) (2020)
- [What Will Your Child Look Like? DNA-Net: Age and Gender Aware Kin Face Synthesizer](https://mlsanity.com/paper/1911.07014/) (2019)
- [Recognizing Families In the Wild: White Paper for the 4th Edition Data Challenge](https://mlsanity.com/paper/2002.06303/) (2020)
- [From Same Photo: Cheating on Visual Kinship Challenges](https://mlsanity.com/paper/1809.06200/) (2018)
- [Challenge report: Recognizing Families In the Wild Data Challenge](https://mlsanity.com/paper/2006.00154/) (2020)
- [A Multi-Task Comparator Framework for Kinship Verification](https://mlsanity.com/paper/2006.01615/) (2020)
- [Multi-view Deep Features for Robust Facial Kinship Verification](https://mlsanity.com/paper/2006.01315/) (2020)
- [Retrieval of Family Members Using Siamese Neural Network](https://mlsanity.com/paper/2006.00174/) (2020)
- [Automatic Face Understanding: Recognizing Families in Photos](https://mlsanity.com/paper/2102.08941/) (2021)

## Built on by (most cited first, 4 of 4)

- [Young Labeled Faces in the Wild (YLFW): A Dataset for Children Faces Recognition](https://mlsanity.com/paper/2301.05776/) (2023)
- [Computer Vision for Multimedia Geolocation in Human Trafficking Investigation: A Systematic Literature Review](https://mlsanity.com/paper/2402.15448/) (2024)
- [Confidence-Calibrated Face and Kinship Verification](https://mlsanity.com/paper/2210.13905/) (2022)
- [KFC: Kinship Verification with Fair Contrastive Loss and Multi-Task Learning](https://mlsanity.com/paper/2309.10641/) (2023)

## Abstract (arXiv)

Recognizing Families In the Wild (RFIW), held as a data challenge in conjunction with the 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG), is a large-scale, multi-track visual kinship recognition evaluation. For the fifth edition of RFIW, we continue to attract scholars, bring together professionals, publish new work, and discuss prospects. In this paper, we summarize submissions for the three tasks of this year's RFIW: specifically, we review the results for kinship verification, tri-subject verification, and family member search and retrieval. We look at the RFIW problem, share current efforts, and make recommendations for promising future directions.