Young Labeled Faces in the Wild (YLFW): A Dataset for Children Faces Recognition

Medvedev, Iurii; Shadmand, Farhad; Gonçalves, Nuno

doi:10.1109/fg59268.2024.10582021

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2024

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Cited by 3 publications

References 43 publications

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SynChildFace: Fine-tuning Face Recognition for Children with Synthetic Data

Kouam,

Rathgeb,

Ibsen

et al. 2024

2024 IEEE International Workshop on Information Forensics and Security (WIFS)

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SynChildFace: Fine-tuning Face Recognition for Children with Synthetic Data

Kouam,

Rathgeb,

Ibsen

et al. 2024

2024 IEEE International Workshop on Information Forensics and Security (WIFS)

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Lip Abnormality Detection for Patients with Repaired Cleft Lip and Palate: A Lip Normalization Approach

Rosero,

Salman,

Hallac

et al. 2024

International Conference on Multimodel Interaction

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COMSATS Face

Haq,

Sethi,

Shahzad

et al. 2024

Deep Cognitive Modelling in Remote Sensing Image Processing

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The human face can appear different depending on the circumstances because of its flexibility and three-dimensional structure. Researchers are facing several obstacles relating to face poses, illumination, facial expressions, head direction, occlusion, hairdo, etc. in the process of developing dependable and efficient algorithms for face detection, face identification, and face expression analysis. To determine the algorithms' effectiveness, they need to be evaluated against a certain set of face image/database benchmarks. This work introduces a dataset of multiple-pose facial photographs. Eight hundred fifty photos from 50 people in 17 distinct stances are included in the collection (0°, 5°, 10°, 15°, 20°, 25°, 30°, 35°, 55°, -5°, -10°, -15°, -20°, -25°, -30°, -35°, -55°). Three distinct lighting conditions are also included in the dataset. Eight resolutions (144 × 256, 200 × 200, 100 × 100, 70 × 70, 50 × 50, 40 × 40, 20 × 20 and 10 × 10 pixels) are available for the dataset. This dataset's facial image content can provide insight on the effectiveness and resilience of upcoming face detection and recognition systems. Additionally, based on the suggested face database, a comparison study of two face recognition methods, such as PAL and PCA, is performed.

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Young Labeled Faces in the Wild (YLFW): A Dataset for Children Faces Recognition

Cited by 3 publications

References 43 publications

SynChildFace: Fine-tuning Face Recognition for Children with Synthetic Data

SynChildFace: Fine-tuning Face Recognition for Children with Synthetic Data

Lip Abnormality Detection for Patients with Repaired Cleft Lip and Palate: A Lip Normalization Approach

COMSATS Face

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