WSD: Wild Selfie Dataset for Face Recognition in Selfie Images
Laxman Kumarapu, Shiv Ram Dubey, Snehasis Mukherjee, Parkhi Mohan,, Sree Pragna Vinnakoti, Subhash Karthikeya

TL;DR
The paper introduces the Wild Selfie Dataset (WSD), a large, challenging collection of selfie images capturing various real-world conditions to advance face recognition research in selfies.
Contribution
It provides a new, extensive dataset with diverse selfie images and challenges, enabling improved face recognition methods tailored for selfies.
Findings
Existing face recognition methods perform poorly on WSD.
WSD contains over 45,000 images with diverse challenges.
The dataset highlights the need for specialized face recognition approaches.
Abstract
With the rise of handy smart phones in the recent years, the trend of capturing selfie images is observed. Hence efficient approaches are required to be developed for recognising faces in selfie images. Due to the short distance between the camera and face in selfie images, and the different visual effects offered by the selfie apps, face recognition becomes more challenging with existing approaches. A dataset is needed to be developed to encourage the study to recognize faces in selfie images. In order to alleviate this problem and to facilitate the research on selfie face images, we develop a challenging Wild Selfie Dataset (WSD) where the images are captured from the selfie cameras of different smart phones, unlike existing datasets where most of the images are captured in controlled environment. The WSD dataset contains 45,424 images from 42 individuals (i.e., 24 female and 18 male…
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Taxonomy
TopicsFace recognition and analysis · Biometric Identification and Security · Facial Nerve Paralysis Treatment and Research
MethodsTest
