Fast facial landmark detection and applications: A survey
K Khabarlak, L Koriashkina - arXiv preprint arXiv:2101.10808, 2021 - arxiv.org
Dense facial landmark detection is one of the key elements of face processing pipeline. It is
used in virtual face reenactment, emotion recognition, driver status tracking, etc. Early …
used in virtual face reenactment, emotion recognition, driver status tracking, etc. Early …
SPARE: Self-supervised part erasing for ultra-fine-grained visual categorization
This paper presents SPARE, a self-supervised part erasing framework for ultra-fine-grained
visual categorization. The key insight of our model is to learn discriminative representations …
visual categorization. The key insight of our model is to learn discriminative representations …
Maskcov: A random mask covariance network for ultra-fine-grained visual categorization
Ultra-fine-grained visual categorization (ultra-FGVC) categorizes objects with more similar
patterns between classes than those in fine-grained visual categorization (FGVC), eg, where …
patterns between classes than those in fine-grained visual categorization (FGVC), eg, where …
Continuous landmark detection with 3d queries
Neural networks for facial landmark detection are notoriously limited to a fixed set of
landmarks in a dedicated layout, which must be specified at training time. Dedicated …
landmarks in a dedicated layout, which must be specified at training time. Dedicated …
Ssfe-net: Self-supervised feature enhancement for ultra-fine-grained few-shot class incremental learning
Abstract Ultra-Fine-Grained Visual Categorization (ultra-FGVC) has become a popular
problem due to its great real-world potential for classifying the same or closely related …
problem due to its great real-world potential for classifying the same or closely related …
Fully automated deep learning models with smartphone applicability for prediction of pain using the Feline Grimace Scale
PV Steagall, BP Monteiro, S Marangoni, M Moussa… - Scientific Reports, 2023 - nature.com
This study used deep neural networks and machine learning models to predict facial
landmark positions and pain scores using the Feline Grimace Scale©(FGS). A total of 3447 …
landmark positions and pain scores using the Feline Grimace Scale©(FGS). A total of 3447 …
Multi-instance semantic similarity transferring for knowledge distillation
Abstract Knowledge distillation is a popular paradigm for learning portable neural networks
by transferring the knowledge from a large model into a smaller one. Most existing …
by transferring the knowledge from a large model into a smaller one. Most existing …
Computation-efficient knowledge distillation via uncertainty-aware mixup
Abstract Knowledge distillation (KD) has emerged as an essential technique not only for
model compression, but also other learning tasks such as continual learning. Given the …
model compression, but also other learning tasks such as continual learning. Given the …
Transformer-based 3d face reconstruction with end-to-end shape-preserved domain transfer
Learning-based face reconstruction methods have recently shown promising performance in
recovering face geometry from a single image. However, the lack of training data with 3D …
recovering face geometry from a single image. However, the lack of training data with 3D …
Interpreting adversarial examples and robustness for deep learning-based auto-driving systems
Deep learning-based auto-driving systems are vulnerable to adversarial examples attacks
which may result in wrong decision making and accidents. An adversarial example can fool …
which may result in wrong decision making and accidents. An adversarial example can fool …