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Past, present, and future of face recognition: A review
Face recognition is one of the most active research fields of computer vision and pattern
recognition, with many practical and commercial applications including identification, access …
recognition, with many practical and commercial applications including identification, access …
Deep learning for computer vision: A brief review
Over the last years deep learning methods have been shown to outperform previous state‐of‐
the‐art machine learning techniques in several fields, with computer vision being one of the …
the‐art machine learning techniques in several fields, with computer vision being one of the …
Disentangled representation learning for multimodal emotion recognition
Multimodal emotion recognition aims to identify human emotions from text, audio, and visual
modalities. Previous methods either explore correlations between different modalities or …
modalities. Previous methods either explore correlations between different modalities or …
A survey on deep learning based face recognition
Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …
increasing interests in face recognition recently, and a number of deep learning methods …
Learning to compare: Relation network for few-shot learning
We present a conceptually simple, flexible, and general framework for few-shot learning,
where a classifier must learn to recognise new classes given only few examples from each …
where a classifier must learn to recognise new classes given only few examples from each …
Deep face recognition: A survey
Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …
multiple levels of feature extraction. This emerging technique has reshaped the research …
Biometrics recognition using deep learning: A survey
In the past few years, deep learning-based models have been very successful in achieving
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …
Feature transfer learning for face recognition with under-represented data
Despite the large volume of face recognition datasets, there is a significant portion of
subjects, of which the samples are insufficient and thus under-represented. Ignoring such …
subjects, of which the samples are insufficient and thus under-represented. Ignoring such …
Agedb: the first manually collected, in-the-wild age database
Over the last few years, increased interest has arisen with respect to age-related tasks in the
Computer Vision community. As a result, several" in-the-wild" databases annotated with …
Computer Vision community. As a result, several" in-the-wild" databases annotated with …
A discriminative feature learning approach for deep face recognition
Convolutional neural networks (CNNs) have been widely used in computer vision
community, significantly improving the state-of-the-art. In most of the available CNNs, the …
community, significantly improving the state-of-the-art. In most of the available CNNs, the …