Mix-ViT: Mixing attentive vision transformer for ultra-fine-grained visual categorization
Ultra-fine-grained visual categorization (ultra-FGVC) moves down the taxonomy level to
classify sub-granularity categories of fine-grained objects. This inevitably poses a challenge …
classify sub-granularity categories of fine-grained objects. This inevitably poses a challenge …
PLFace: Progressive learning for face recognition with mask bias
The outbreak of the COVID-19 coronavirus epidemic has promoted the development of
masked face recognition (MFR). Nevertheless, the performance of regular face recognition is …
masked face recognition (MFR). Nevertheless, the performance of regular face recognition is …
Vision Sensing-Driven Intelligent Ocular Disease Detection Using Conformer-Based Dual Fusion
The deep vision sensing has been a practical tool in early disease detection, and this work
aims at an important branch of ocular disease recognition. Although a number of …
aims at an important branch of ocular disease recognition. Although a number of …
Seg-dgdnet: Segmentation based disguise guided dropout network for low resolution face recognition
Face recognition models often encounter challenges while recognizing partially occluded
faces. Disguise can be manifested intentionally to impersonate someone or unintentionally …
faces. Disguise can be manifested intentionally to impersonate someone or unintentionally …
An interpretable channelwise attention mechanism based on asymmetric and skewed gaussian distribution
C Chen, B Li - Pattern Recognition, 2023 - Elsevier
Channelwise attention mechanisms have recently been demonstrated to boost the
performance of deep convolutional neural networks (CNNs). The hypothesis on the negative …
performance of deep convolutional neural networks (CNNs). The hypothesis on the negative …
Unlabeled data assistant: improving mask robustness for face recognition
The existing masked face recognition algorithms almost tend to adopt synthetic masked face
datasets for training. However, these models are limited as they rely on existing mask …
datasets for training. However, these models are limited as they rely on existing mask …
MaskDUF: Data uncertainty learning in masked face recognition with mask uncertainty fluctuation
M Zhong, W **ong, D Li, K Chen, L Zhang - Expert Systems with …, 2024 - Elsevier
As an essential component of experts and intelligent systems, Masked Face Recognition
(MFR) has been applied to various applications, but it is still a challenging task due to the …
(MFR) has been applied to various applications, but it is still a challenging task due to the …
Joint holistic and masked face recognition
With the widespread use of face masks due to the COVID-19 pandemic, accurate masked
face recognition has become more crucial than ever. While several studies have …
face recognition has become more crucial than ever. While several studies have …
Consistent sub-decision network for low-quality masked face recognition
The COVID-19 pandemic makes wearing masks mandatory in supermarkets, pharmacies,
public transport, etc. Existing facial recognition systems encounter severe performance …
public transport, etc. Existing facial recognition systems encounter severe performance …
Masked face transformer
The COVID-19 pandemic makes wearing masks mandatory. Existing CNN-based face
recognition (FR) systems suffer from severe performance degradation as masks occlude the …
recognition (FR) systems suffer from severe performance degradation as masks occlude the …