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Fast Facial Landmark Detection and Applications: A Survey

Journal of Computer Science and Technology, 2022
Dense facial landmark detection is a key element of face processing pipeline. In this paper we survey and analyze modern neural-network-based facial landmark detection algorithms, focus on approaches that have led to a significant increase in quality ...
Kostiantyn Khabarlak, Larysa Koriashkina
doaj   +4 more sources

Facial Landmark Detection: A Literature Survey [PDF]

International Journal of Computer Vision, 2018
The locations of the fiducial facial landmark points around facial components and facial contour capture the rigid and non-rigid facial deformations due to head movements and facial expressions. They are hence important for various facial analysis tasks.
Qiang Ji, Yue Wu
exaly   +3 more sources

Combining CNNs and Markov-like Models for Facial Landmark Detection with Spatial Consistency Estimates [PDF]

Journal of Imaging, 2023
The accurate localization of facial landmarks is essential for several tasks, including face recognition, head pose estimation, facial region extraction, and emotion detection.
Ahmed Gdoura, Markus Degünther, Birgit Lorenz, Alexander Effland   +3 more
doaj   +2 more sources

Dilated Skip Convolution for Facial Landmark Detection. [PDF]

Sensors (Basel), 2019
Facial landmark detection has gained enormous interest for face-related applications due to its success in facial analysis tasks such as facial recognition, cartoon generation, face tracking and facial expression analysis. Many studies have been proposed and implemented to deal with the challenging problems of localizing facial landmarks from given ...
Chim S, Lee JG, Park HH.
europepmc   +4 more sources

2D Wasserstein loss for robust facial landmark detection [PDF]

Pattern Recognition, 2021
The recent performance of facial landmark detection has been significantly improved by using deep Convolutional Neural Networks (CNNs), especially the Heatmap Regression Models (HRMs). Although their performance on common benchmark datasets has reached a high level, the robustness of these models still remains a challenging problem in the practical use
Christophe Garcia, Stefan Duffner, Anthony Berthelier   +2 more
exaly   +3 more sources

Feature fusion for facial landmark detection

Pattern Recognition, 2014
Abstract Facial landmark detection is a crucial first step in facial analysis for biometrics and numerous other applications. However, it has proved to be a very challenging task due to the numerous sources of variation in 2D and 3D facial data.
Ioannis A Kakadiaris, Panagiotis Perakis, Theoharis Theoharis   +2 more
exaly   +3 more sources

Dog facial landmarks detection and its applications for facial analysis

Scientific Reports
Automated analysis of facial expressions is a crucial challenge in the emerging field of animal affective computing. One of the most promising approaches in this context is facial landmarks, which are well-studied for humans and are now being adopted for
George Martvel, Anna Zamansky, Giulia Pedretti, Chiara Canori, Ilan Shimshoni, Annika Bremhorst   +5 more
doaj   +3 more sources

HybridMatch: Semi-Supervised Facial Landmark Detection via Hybrid Heatmap Representations

IEEE Access, 2023
Facial landmark detection is an essential task in face-processing techniques. Traditional methods, however, require expensive pixel-level labels. Semi-supervised facial landmark detection has been explored as an alternative, but previous approaches only ...
Seoungyoon Kang, Minhyun Lee, Minjae Kim, Hyunjung Shim   +3 more
doaj   +1 more source

Detecting Facial Region and Landmarks at Once via Deep Network

Sensors, 2021
For accurate and fast detection of facial landmarks, we propose a new facial landmark detection method. Previous facial landmark detection models generally perform a face detection step before landmark detection.
Taehyung Kim, Jiwon Mok, Euichul Lee
doaj   +1 more source

Design of a Facial Landmark Detection System Using a Dynamic Optical Flow Approach

IEEE Access, 2021
Many facial landmark methods based on convolutional neural networks (CNN) have been proposed to achieve favorable detection results. However, the instability landmarks that occur in video frames due to CNNs are extremely sensitive to input image noise ...
Bing-Fei Wu, Bo-Rui Chen, Chun-Fei Hsu
doaj   +1 more source