Face recognition by humans and machines: three fundamental advances from deep learning
AJ O'Toole, CD Castillo - Annual Review of Vision Science, 2021 - annualreviews.org
Deep learning models currently achieve human levels of performance on real-world face
recognition tasks. We review scientific progress in understanding human face processing …
recognition tasks. We review scientific progress in understanding human face processing …
A star-nose-like tactile-olfactory bionic sensing array for robust object recognition in non-visual environments
M Liu, Y Zhang, J Wang, N Qin, H Yang, K Sun… - Nature …, 2022 - nature.com
Object recognition is among the basic survival skills of human beings and other animals. To
date, artificial intelligence (AI) assisted high-performance object recognition is primarily …
date, artificial intelligence (AI) assisted high-performance object recognition is primarily …
3d morphable face models—past, present, and future
In this article, we provide a detailed survey of 3D Morphable Face Models over the 20 years
since they were first proposed. The challenges in building and applying these models …
since they were first proposed. The challenges in building and applying these models …
Fast identification of fluorescent components in three-dimensional excitation-emission matrix fluorescence spectra via deep learning
Three-dimensional excitation-emission matrix (3D-EEM) fluorescence spectroscopy has
been widely applied to detect the fluorescent components in samples from natural water …
been widely applied to detect the fluorescent components in samples from natural water …
Diverse types of expertise in facial recognition
Facial recognition errors can jeopardize national security, criminal justice, public safety and
civil rights. Here, we compare the most accurate humans and facial recognition technology …
civil rights. Here, we compare the most accurate humans and facial recognition technology …
The face of image reconstruction: progress, pitfalls, prospects
Recent research has demonstrated that neural and behavioral data acquired in response to
viewing face images can be used to reconstruct the images themselves. However, the …
viewing face images can be used to reconstruct the images themselves. However, the …
Pass: protected attribute suppression system for mitigating bias in face recognition
Face recognition networks encode information about sensitive attributes while being trained
for identity classification. Such encoding has two major issues:(a) it makes the face …
for identity classification. Such encoding has two major issues:(a) it makes the face …
Gradient attention balance network: Mitigating face recognition racial bias via gradient attention
Although face recognition has made impressive progress in recent years, we ignore the
racial bias of the recognition system when we pursue a high level of accuracy. Previous …
racial bias of the recognition system when we pursue a high level of accuracy. Previous …
Beyond identity: What information is stored in biometric face templates?
Deeply-learned face representations enable the success of current face recognition
systems. Despite the ability of these representations to encode the identity of an individual …
systems. Despite the ability of these representations to encode the identity of an individual …
Understanding the role of eye movement consistency in face recognition and autism through integrating deep neural networks and hidden Markov models
Greater eyes-focused eye movement pattern during face recognition is associated with
better performance in adults but not in children. We test the hypothesis that higher eye …
better performance in adults but not in children. We test the hypothesis that higher eye …