Recognizing Families In the Wild (RFIW): The 4th Edition

Recognizing Families In the Wild (RFIW)– an annual large-scale, multi-track automatic kinship recognition evaluation– supports various visual kin-based problems on scales much higher than ever before. Organized in conjunction with the as a Challenge, RFIW provides a platform for publishing original work and the gathering of experts for a discussion of the next steps. This paper summarizes the supported tasks (i.e., kinship verification, tri-subject verification, and search & retrieval of missing children) in the evaluation protocols, which include the practical motivation, technical background, data splits, metrics, and benchmark results. Furthermore, top submissions (i.e., leader-board stats) are listed and reviewed as a high-level analysis on the state of the problem. In the end, the purpose of this paper is to describe the 2020 RFIW challenge, end-to-end, along with forecasts in promising future directions.

[1]  Marwan Mattar,et al.  Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments , 2008 .

[2]  Li Bai,et al.  Cosine Similarity Metric Learning for Face Verification , 2010, ACCV.

[3]  Tsuhan Chen,et al.  Towards computational models of kinship verification , 2010, 2010 IEEE International Conference on Image Processing.

[4]  Ming Shao,et al.  Genealogical face recognition based on UB KinFace database , 2011, CVPR 2011 WORKSHOPS.

[5]  Ming Shao,et al.  Kinship Verification through Transfer Learning , 2011, IJCAI.

[6]  Jiebo Luo,et al.  Understanding Kin Relationships in a Photo , 2012, IEEE Transactions on Multimedia.

[7]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[8]  Jiwen Lu,et al.  Neighborhood repulsed metric learning for kinship verification , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Ming Shao,et al.  Low-Rank Transfer Subspace Learning , 2012, 2012 IEEE 12th International Conference on Data Mining.

[10]  Tsuhan Chen,et al.  Kinship classification by modeling facial feature heredity , 2013, 2013 IEEE International Conference on Image Processing.

[11]  Andrew Zisserman,et al.  Deep Face Recognition , 2015, BMVC.

[12]  Liang Wang,et al.  Kinship Verification with Deep Convolutional Neural Networks , 2015, BMVC.

[13]  James Philbin,et al.  FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[14]  Jiwen Lu,et al.  The FG 2015 Kinship Verification in the Wild Evaluation , 2015, 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).

[15]  Xiaoyang Tan,et al.  Tri-subjects kinship verification: Understanding the core of a family , 2015, 2015 14th IAPR International Conference on Machine Vision Applications (MVA).

[16]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[17]  Yuxiao Hu,et al.  MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition , 2016, ECCV.

[18]  Forrest N. Iandola,et al.  SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size , 2016, ArXiv.

[19]  Abdenour Hadid,et al.  Comments on the “Kinship Face in the Wild” Data Sets , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Ming Shao,et al.  Families in the Wild (FIW): Large-Scale Kinship Image Database and Benchmarks , 2016, ACM Multimedia.

[21]  Anil K. Jain,et al.  IARPA Janus Benchmark-B Face Dataset , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[22]  Handong Zhao,et al.  Recognizing Families In the Wild (RFIW): Data Challenge Workshop in conjunction with ACM MM 2017 , 2017 .

[23]  S. Shan,et al.  KinNet: Fine-to-Coarse Deep Metric Learning for Kinship Verification , 2017 .

[24]  Qingyan Duan,et al.  AdvNet: Adversarial Contrastive Residual Net for 1 Million Kinship Recognition , 2017 .

[25]  Hamdi Dibeklioglu,et al.  What Will Your Future Child Look Like? Modeling and Synthesis of Hereditary Patterns of Facial Dynamics , 2017, 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017).

[26]  Yun Fu,et al.  Kinship Verification on Families in the Wild with Marginalized Denoising Metric Learning , 2017, 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017).

[27]  Bhiksha Raj,et al.  SphereFace: Deep Hypersphere Embedding for Face Recognition , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[28]  Yun Fu,et al.  Kinship Classification through Latent Adaptive Subspace , 2018, 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018).

[29]  Savas Özkan,et al.  Kinshipgan: Synthesizing of Kinship Faces from Family Photos by Regularizing a Deep Face Network , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).

[30]  Omkar M. Parkhi,et al.  VGGFace2: A Dataset for Recognising Faces across Pose and Age , 2017, 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018).

[31]  Andrew Zisserman,et al.  From Same Photo: Cheating on Visual Kinship Challenges , 2018, ACCV.

[32]  Ming Shao,et al.  Visual Kinship Recognition of Families in the Wild , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[33]  Ming Shao,et al.  To Recognize Families In the Wild: A Machine Vision Tutorial , 2018, ACM Multimedia.

[34]  Yun Fu,et al.  Cross-Generation Kinship Verification with Sparse Discriminative Metric , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  Fang Zhao,et al.  Multi-Prototype Networks for Unconstrained Set-based Face Recognition , 2019, IJCAI.

[36]  Ning Zhang,et al.  Laplace Landmark Localization , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[37]  Min Xu,et al.  Adversarial Similarity Metric Learning for Kinship Verification , 2019, IEEE Access.

[38]  Stefanos Zafeiriou,et al.  ArcFace: Additive Angular Margin Loss for Deep Face Recognition , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[39]  Abdelmalik Taleb-Ahmed,et al.  Multi-view Deep Features for Robust Facial Kinship Verification , 2020, 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020).

[40]  Geoffrey E. Hinton,et al.  A Simple Framework for Contrastive Learning of Visual Representations , 2020, ICML.

[41]  Gerhard Rigoll,et al.  A Multi-Task Comparator Framework for Kinship Verification , 2020, 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020).

[42]  Jun Yu,et al.  Retrieval of Family Members Using Siamese Neural Network , 2020, 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020).

[43]  Face Recognition: Too Bias, or Not Too Bias? , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[44]  Zhipeng Luo,et al.  Challenge report Recognizing Families In the Wild Data Challenge , 2020, 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020).

[45]  Chetan Kumar,et al.  Adversary for Social Good: Protecting Familial Privacy through Joint Adversarial Attacks , 2020, AAAI.

[46]  Andrei Shadrikov,et al.  Achieving Better Kinship Recognition Through Better Baseline , 2020, 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020).

[47]  Enhua Wu,et al.  Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[48]  Jun Yu,et al.  Deep Fusion Siamese Network for Automatic Kinship Verification , 2020, 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020).

[49]  Mei Wang,et al.  Deep Face Recognition: A Survey , 2018, Neurocomputing.

[50]  Joseph P. Robinson,et al.  Survey on the Analysis and Modeling of Visual Kinship: A Decade in the Making , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[51]  Iddo Drori,et al.  Top 3 in FG 2021 Families In the Wild Kinship Verification Challenge , 2021, ArXiv.

[52]  Ming Shao,et al.  Families in Wild Multimedia: A Multimodal Database for Recognizing Kinship , 2020, IEEE Transactions on Multimedia.

[53]  Yun Fu,et al.  Balancing Biases and Preserving Privacy on Balanced Faces in the Wild , 2021, ArXiv.

[54]  Joseph P Robinson.  Automatic Face Understanding: Recognizing Families in Photos , 2021, ArXiv.

[55]  Wojciech Zaremba,et al.  Evaluating Large Language Models Trained on Code , 2021, ArXiv.

[56]  J. Paul Robinson,et al.  What Will Your Child Look Like? DNA-Net: Age and Gender Aware Kin Face Synthesizer , 2019, ArXiv.

[57]  Guodong Guo,et al.  Supervised Contrastive Learning for Facial Kinship Recognition , 2021, 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021).

[58]  Guochen Xie,et al.  Deep Kinship Verification and Retrieval Based on Fusion Siamese Neural Network , 2021, 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021).