Deep face recognition: A survey
Mei Wang,Weihong Deng +1 more
TLDR
A comprehensive review of the recent developments on deep face recognition can be found in this paper, covering broad topics on algorithm designs, databases, protocols, and application scenes, as well as the technical challenges and several promising directions.About:
This article is published in Neurocomputing.The article was published on 2021-03-14 and is currently open access. It has received 353 citations till now. The article focuses on the topics: Deep learning & Feature extraction.read more
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One Shot Audio to Animated Video Generation.
Neeraj Kumar,Srishti Goel,Ankur Narang,Brejesh Lall,Hasan Mujtaba,Pranshu Agarwal,Dipankar Sarkar +6 more
TL;DR: OneShotAu2AV as mentioned in this paper uses an audio clip and a single unseen image of a person as an input for unsupervised audio to animated video generation, which can generate animated videos that have natural facial expressions such as blinks and eyebrow movements, and head movements.
Book ChapterDOI
Dormitory Management System Based on Face Recognition
TL;DR: In this article, a face recognition system for dormitory management is proposed, which realizes the function of entering and leaving dormitory through face voucher, storing the information of students, and automatically updating relevant data.
Journal ArticleDOI
Analysis of Real-Time Face-Verification Methods for Surveillance Applications
Filiberto Perez-Montes,Jesus Olivares-Mercado,Gabriel Sánchez Pérez,Gibran Benitez-Garcia,Lidia Prudente-Tixteco,Osvaldo Lopez-Garcia +5 more
TL;DR: Wang et al. as mentioned in this paper compared three SOTA real-time face-verification methods for coping with specific problems in surveillance applications and found that EfficientNet-B0 was better at handling extreme face rotation over 80 degrees.
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Evaluation of Human and Machine Face Detection using a Novel Distinctive Human Appearance Dataset.
Necdet Gurkan,Jordan W. Suchow +1 more
TL;DR: In this paper, the Distinctive Human Appearance (DHA) dataset is used to evaluate the performance of face detection models. But, the evaluation results show that face detection algorithms do not generalize well to these diverse appearances.
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Fine-Grained Image Analysis with Deep Learning: A Survey
Xiu-Shen Wei,Yi-Zhe Song,Oisin Mac Aodha,Jianxin Wu,Yuxin Peng,Jinhui Tang,Jian Yang,Serge Belongie +7 more
TL;DR: In this paper, a systematic survey of fine-grained image analysis is presented, where the authors attempt to re-define and broaden the field of FGIA by consolidating two fundamental finegrained research areas.
References
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Proceedings Article
Very Deep Convolutional Networks for Large-Scale Image Recognition
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