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Article
Computer Science, Artificial Intelligence
Ali Pourramezan Fard et al.
Summary: Facial landmark detection is a crucial step in facial image analysis. This paper presents a novel loss function and utilizes knowledge distillation to train a lightweight student network for this task, achieving high accuracy by combining two teacher networks and a student network with defined assistive loss functions.
COMPUTER VISION AND IMAGE UNDERSTANDING
(2022)
Article
Computer Science, Artificial Intelligence
Kanglin Liu et al.
Summary: In this paper, a new technique called STIA-WO is presented to disentangle the latent space for unsupervised semantic face editing. By applying STIA-WO to GAN, a StyleGAN named STGAN-WO is developed, which achieves better attribute editing than state of the art methods.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Computer Science, Artificial Intelligence
Xianxu Hou et al.
Summary: This paper proposes a novel learning framework called GuidedStyle for semantic face editing on pretrained StyleGAN, guiding the image generation process with a knowledge network and allowing an attention mechanism for style manipulation. The method demonstrates superior results in disentangled and controllable edits along various attributes, showcasing strong generalization ability for different types of real and artistic face editing.
Article
Computer Science, Artificial Intelligence
Jinyan Ma et al.
Summary: The proposed face alignment algorithm DSCN combines capsule network and attention mechanism to address occlusion issues, achieving low failure rates and small mean errors on multiple datasets.
PATTERN RECOGNITION
(2022)
Article
Computer Science, Artificial Intelligence
Congcong Zhu et al.
Summary: This paper proposes a structural relation network (SRN) for occlusion-robust landmark localization, which aims to capture the structural relations among different facial components to improve localization accuracy. The method considers spatial relations in model design, enhances training data by synthesizing occluded faces, and extends the ability to handle occluded video data using a Markov decision process.
PATTERN RECOGNITION
(2022)
Article
Computer Science, Artificial Intelligence
Huabin Wang et al.
Summary: This paper proposes a multistage model based on deep neural networks for face alignment, utilizing spatial transformer networks, hourglass networks, and exemplar-based shape constraints to address initialization issues and improve performance in challenging conditions such as rotation and scale variations. Experimental results demonstrate the superior performance of the proposed method over other state-of-the-art methods on challenging benchmark datasets.
COGNITIVE COMPUTATION
(2022)
Article
Automation & Control Systems
Fu Xiong et al.
Summary: A novel ensemble cascade metric-learning mechanism is proposed, utilizing hierarchical metric learning to alleviate underfitting and executing metric learning among feature groups to resist overfitting, improving the performance of face verification.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Engineering, Electrical & Electronic
Maneet Singh et al.
Summary: With the increasing usage of face recognition algorithms, recognizing disguised faces has become one of the most challenging tasks. This paper proposes a novel encoder-decoder network, called DED-Net, which learns the class variations in the feature space generated by disguised and non-disguised images. The proposed D-Res framework achieves superior performance in disguise recognition and low resolution settings, as demonstrated on benchmark datasets.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Yanjing Lu et al.
Summary: In this study, a face recognition algorithm based on LBP and stacked autoencoder is proposed to optimize the weak robustness of traditional algorithms. The experimental results demonstrate that this algorithm achieves high recognition rates and better performance compared to classic algorithms.
JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Xiaoqian Yue et al.
Summary: Face alignment is a challenging task in computer vision due to large pose variations, occlusions, and lighting. The Multi-task Adversarial Autoencoder (MTAAE) network is proposed to learn representative facial appearance for heatmap regression, improving face alignment performance. MTAAE utilizes three tasks and dynamic weights to outperform state-of-the-art methods in complex environments.
Article
Computer Science, Artificial Intelligence
Haifeng Zhang et al.
Summary: This article proposes an identity-expression dual branch network (IE-DBN) for facial expression recognition, which learns identity-related features and expression-related features from the same input facial expression image through two branches and aggregates them with a bilinear module to improve recognition accuracy.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Jun Wan et al.
Summary: The paper introduces a CCDN for robust facial landmark detection, which enhances semantic feature learning by introducing the CTM module and COCS regularizer to learn more fine and complementary features, improving accuracy under extremely challenging scenarios.
Article
Computer Science, Artificial Intelligence
Boyu Chen et al.
Summary: The paper introduces a residual multi-task learning framework for predicting facial landmark localization and expression recognition simultaneously, utilizing a residual learning module to strengthen the connection between the two tasks and addressing the lack of training data with multi-task labels in multi-task learning.
PATTERN RECOGNITION
(2021)
Article
Computer Science, Artificial Intelligence
Hao Liu et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2020)
Article
Optics
Mohammed Ahmed Talab et al.
INTERNATIONAL JOURNAL OF OPTICS
(2020)
Article
Computer Science, Information Systems
Adel Saoud et al.
MULTIMEDIA TOOLS AND APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Zhaoli Zhang et al.
Article
Computer Science, Artificial Intelligence
Hongyu Zhu et al.
PATTERN RECOGNITION
(2020)
Proceedings Paper
Imaging Science & Photographic Technology
Weiliang Chen et al.
2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
(2019)
Article
Computer Science, Artificial Intelligence
Baoguang Shi et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2018)
Article
Computer Science, Artificial Intelligence
Byung-Hwa Park et al.
EXPERT SYSTEMS WITH APPLICATIONS
(2017)
Article
Computer Science, Artificial Intelligence
Qingshan Liu et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2017)
Article
Computer Science, Artificial Intelligence
Shaoqing Ren et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2016)
Article
Computer Science, Artificial Intelligence
Zhanpeng Zhang et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2016)
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Computer Science, Artificial Intelligence
TF Cootes et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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