Deep Learning for Human-Centric Computer Vision
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: closed (25 January 2023) | Viewed by 14533
Special Issue Editors
2. Center of Materials Science and Optoelectronics Engineering School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing 100049, China
Interests: pattern recognition; image classification; neural network; convolutional network; computer vision; object detection
Special Issues, Collections and Topics in MDPI journals
Interests: pattern recognition, computational intelligence and its applications in intelligent healthcare
2. School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China
Interests: neural networks; forecast modeling; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Deep learning has been widely used in massive applications, such as natural language processing, computer vision, decision making, and data security. Among these, the field of computer vision has recently seen rapid development. However, it has been accompanied by certain challenges, such as person re-identification, lip language recognition, makeup transfer, and face image editing. A majority of these challenges belong to the category of human-centric computer vision, which has become an important research topic in academia. Several studies proposing deep learning-based approaches have achieved promising results in solving human-centric computer vision problems.
This Special Issue aims to curate original research and review articles from academia and industry-relevant researchers in the fields of deep learning, image processing, and computer vision. Researchers and industry practitioners from academia are invited to submit their innovative research on technical challenges and state-of-the-art findings related to human-centric computer vision. This Special Issue provides an opportunity to discuss and express views on current trends, challenges, and state-of-the-art solutions to the various problems in human-centric computer vision.
Topic:
- Face recognition;
- Expression recognition and affective computing;
- Face image editing and makeup transfer;
- Finger vein recognition;
- Gait recognition;
- Iris recognition;
- Human pose estimation;
- Pedestrian detection and tracking;
- Person re-identification;
- Gesture recognition;
- Lip language recognition;
- 3D vision face or human body application.
Dr. Xin Ning
Prof. Dr. Yizhang Jiang
Dr. Weiwei Cai
Guest Editors
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Keywords
- deep learning
- computer Vision
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