Article
Multidisciplinary Sciences
Giuseppe Ortolano, Elena Losero, Stefano Pirandola, Marco Genovese, Ivano Ruo-Berchera
Summary: Through theoretical and experimental demonstrations, quantum advantage can be achieved in quantum reading by combining practical photon-counting measurements with a simple maximum-likelihood decision. Quantum entanglement and simple optics are shown to enhance the readout of digital data, paving the way for practical applications of quantum reading.
Article
Optics
Jan Perina, Vaclav Michalek, Radek Machulka, Ondrj Haderka
Summary: Selective post-selection of one beam out of a system of three correlated beams with bi-partite photon-number correlations leads to joint photon-number distributions with checkered patterns. The experimental and theoretical analysis shows nonclassical properties of these states as they vary with the ratio of correlated and anti-correlated contributions, confirmed by 2D histograms reconstructed by maximum-likelihood approach. The investigations suggest potential applications in two-photon excitations of atoms and molecules as well as two-photon spectroscopy.
Article
Optics
Zhaoshuai Qi, Jingqi Pang, Yifeng Hao, Yanning Zhang
Summary: We propose an inter-sphere consistency-based method for camera-projector pairs calibration, which extracts additional constraints from consistency between estimated parameters from different spheres. This enables flexible and easy calibration using only two spheres, addressing a challenging problem.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Giuseppe Ortolano, Pauline Boucher, Ivo Pietro Degiovanni, Elena Losero, Marco Genovese, Ivano Ruo-Berchera
Summary: A protocol addressing the conformance test problem is introduced, showing that a simple quantum strategy can outperform any classical strategy. The experimental implementation of this protocol using optical twin beams validates the theoretical results and demonstrates a quantum advantage in a realistic setting.
Article
Mathematics
Luis-Rogelio Roman-Rivera, Israel Sotelo-Rodriguez, Jesus Carlos Pedraza-Ortega, Marco Antonio Aceves-Fernandez, Juan Manuel Ramos-Arreguin, Efren Gorrostieta-Hurtado
Summary: RGB-D cameras are commonly used in 3D reconstruction and computer vision, but calibration errors can affect alignment. In this work, we propose a novel strategy that simplifies calibration by using a known-sized ordinary object as a calibration reference, requiring fewer images and achieving comparable results even in non-ideal conditions.
Article
Optics
Xing Qu, Pengyu Hu, Huiwen Deng, Yu Duan, Shuming Yang
Summary: This paper proposes two methods based on blinking pattern and calibration panel motion to solve the problem of DVS not being able to directly detect traditional control points. The experimental results show that both methods can significantly reduce the standard deviation compared to the conventional methods.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Fengli Yang, Yue Zhao, Xuechun Wang
Summary: This study investigates the pole-polar properties of central catadioptric sphere or line images and proposes a camera calibration algorithm based on the generalized eigenvalue decomposition. The algorithm can effectively recover the pole and polar of the image of absolute conic and the modified image of absolute conic. Furthermore, it is also applicable to paracatadioptric sensors.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2023)
Article
Computer Science, Information Systems
Jonguk Kim, Hyansu Bae, Suk Gyu Lee
Summary: This paper proposes a stereo camera calibration method based on calibration and validation techniques, with experimental results demonstrating its efficiency.
Article
Computer Science, Artificial Intelligence
Jian Yu, Feipeng Da, Wenjian Li
Summary: This paper presents a newly developed calibration algorithm for camera-projector system using spheres. The approach strengthens the calibration for both camera and projector by exploiting image conics of a sphere. The algorithm requires at least 3 image conics on the image plane of each device to calculate intrinsic parameters, and determines extrinsic parameters based on the position of sphere centers in each device's coordinate frame, mainly focusing on calibrating multiple camera-projector systems.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Multidisciplinary Sciences
Victor Vidyapin, Yingwen Zhang, Duncan England, Benjamin Sussman
Summary: We present a simple and effective method to characterize the per pixel quantum efficiency and temporal resolution of a single photon event camera for quantum imaging. Using photon pairs generated through spontaneous parametric down-conversion, we extract the detection efficiency and temporal resolution through coincidence measurements. In evaluating the TPX3CAM with image intensifier, we measure an average efficiency of 7.4 +/- 2% and a temporal resolution of 7.3 ns. This technique also identifies important error mechanisms in post-processing. We believe this method will be valuable for characterizing other quantum imaging systems.
SCIENTIFIC REPORTS
(2023)
Article
Multidisciplinary Sciences
Wei-wei Sheng
Summary: This paper proposes a precise measurement method and corresponding calibration procedure for a line structure light vision sensor with a large measurement range. By utilizing a linear translation stage and planar target, the relationship between the center point of the laser stripe and the perpendicular/horizontal distance is obtained. The proposed method eliminates the need for distortion compensation and significantly improves measurement precision.
SCIENTIFIC REPORTS
(2023)
Article
Optics
P. A. Prudkovskii, D. A. Safronenkov, G. Kh Kitaeva
Summary: We extend the absolute quantum efficiency (QE) calibration method to analog detectors with a high dispersion of single-photon responses. By measuring the biphoton field correlation function and approximating the distribution of detector readings, we demonstrate a reliable measurement of photomultiplier tube (PMT) cathode QE.
Article
Computer Science, Artificial Intelligence
Zhe Zhang, Chunyu Wang, Weichao Qiu, Wenhu Qin, Wenjun Zeng
Summary: AdaFuse is an adaptive multiview fusion method designed to address occlusion challenges in human pose estimation in the wild. It effectively determines point-point correspondences between different views and learns adaptive fusion weights to optimize feature quality. Through evaluations on public datasets, AdaFuse outperforms state-of-the-art methods in all metrics.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2021)
Article
Optics
Ning Yan, Dongxue Wang, Shuangxiong Yin, Zhipeng Guo, Xiaodong Zhang
Summary: Phase measurement deflectometry (PMD) is a high-precision optical surface measurement method that achieves accuracy comparable to interference methods through a simple system structure. By replacing a large screen with two small screens and a single point, the proposed improvements in the traditional binocular PMD method increase system flexibility and measurement accuracy.
Article
Physics, Multidisciplinary
P. A. Prudkovskii
Summary: Theoretical study on the effect of the structure of angular modes in an optical-terahertz biphoton field shows the possibility of determining scattering matrix and relationships between various parameters. This helps in measuring nonclassical correlation properties of the field.
Article
Computer Science, Artificial Intelligence
Guanying Chen, Kai Han, Boxin Shi, Yasuyuki Matsushita, Kwan-Yee K. Wong
Summary: This study addresses the problem of photometric stereo for non-Lambertian surfaces using deep learning, introducing the PS-FCN and LCNet networks. Experimental results show that both models outperform state-of-the-art methods in both calibrated and uncalibrated scenarios.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Engineering, Biomedical
Xihe Kuang, Jason Pui Yin Cheung, Kwan-Yee K. Wong, Wai Yi Lam, Chak Hei Lam, Richard W. Choy, Christopher P. Cheng, Honghan Wu, Cao Yang, Kun Wang, Yang Li, Teng Zhang
Summary: This study proposes a hybrid framework called Spine-GFlow, which combines CNN model learned image features and anatomical priors for multi-tissue segmentation in sagittal lumbar MRI without manual annotation. The experimental results show that this method achieves comparable segmentation performance to fully supervised models.
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
(2022)
Article
Computer Science, Artificial Intelligence
Wenqi Yang, Zhenfang Chen, Chaofeng Chen, Guanying Chen, Kwan-Yee K. Wong
Summary: This paper proposes a two-stage deep learning method for face video inpainting. The first stage performs face inpainting in the UV space to remove the influence of face poses and expressions. The second stage refines the inpainted face regions and inpaints any uncovered background regions. Extensive experiments show that our method outperforms methods based merely on 2D information, especially for faces under large pose and expression variations.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2023)
Article
Computer Science, Artificial Intelligence
Chaofeng Chen, Wei Liu, Xiao Tan, Kwan-Yee K. Wong
Summary: This paper proposes a semi-supervised approach, named Semi-Cycle-GAN (SCG), to tackle the problems of face photo-sketch translation. The approach utilizes a noise-injection strategy and pseudo sketch feature representation to generate high-quality results. It also alleviates the steganography effect and overfitting issues commonly seen in fully supervised approaches.
COMPUTER VISION AND IMAGE UNDERSTANDING
(2023)
Article
Medicine, General & Internal
Nan Meng, Kwan-Yee K. Wong, Moxin Zhao, Jason P. Y. Cheung, Teng Zhang
Summary: This study developed a radiation-free portable system and device using light-based depth sensing and deep learning technologies to analyze Adolescent Idiopathic Scoliosis (AIS). The device can provide instantaneous and accurate spine alignment analysis without radiation exposure, with the potential for integration into routine screening.
Article
Medicine, General & Internal
Nan Meng, Jason P. Y. Cheung, Kwan-Yee K. Wong, Socrates Dokos, Sofia Li, Richard W. Choy, Samuel To, Ricardo J. Li, Teng Zhang
Summary: This study developed a hybrid model called SpineHRNet+ that integrates artificial intelligence and rule-based methods to improve the reliability and interpretability of spine alignment auto-analysis. The results showed that the model achieved accurate landmark detection and strong correlation with ground truth alignment. It has the potential to assist clinical work and facilitate large-scale clinical studies.
Proceedings Paper
Computer Science, Artificial Intelligence
Guanying Chen, Chaofeng Chen, Shi Guo, Zhetong Liang, Kwan-Yee K. Wong, Lei Zhang
Summary: This study introduces a coarse-to-fine deep learning framework for HDR video reconstruction, which includes coarse alignment and pixel blending in the image space followed by more sophisticated alignment and temporal fusion in the feature space to achieve better reconstruction results.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Chaofeng Chen, Xiaoming Li, Lingbo Yang, Xianhui Lin, Lei Zhang, Kwan-Yee K. Wong
Summary: The paper proposes a new progressive semantic-aware style transformation framework, named PSFR-GAN, for face restoration, which can generate high-quality face images by utilizing semantic information and pixel information from different scales of input pairs. By introducing semantic aware style loss and pretraining a face parsing network, the model trained with synthetic data shows better performance in producing high-resolution results and generalizing to natural LQ face images compared to state-of-the-art methods.
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021
(2021)
Article
Computer Science, Information Systems
Teng Zhang, Yifei Li, Jason Pui Yin Cheung, Socrates Dokos, Kwan-Yee K. Wong
Summary: The study developed an automated system using mobile phones to accurately predict Cobb angles and vertebral landmarks on X-ray images despite image quality, showcasing its potential for telemedicine applications. The system demonstrated high accuracy in landmark detection and Cobb angle prediction, providing valuable tools for auto-diagnosis and follow-up in scoliosis patients.
Article
Computer Science, Artificial Intelligence
Kai Han, Miaomiao Liu, Dirk Schnieders, Kwan-Yee K. Wong
Summary: This paper proposes a method based on observing the reflections of a moving reference plane on the mirror surface, which can recover the camera intrinsics, the poses of the reference plane, as well as the mirror surface from the observed reflections of the reference plane under at least three unknown distinct poses. Experimental results demonstrate the feasibility and accuracy of this method.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Computer Science, Artificial Intelligence
Chaofeng Chen, Dihong Gong, Hao Wang, Zhifeng Li, Kwan-Yee K. Wong
Summary: This paper introduces a novel SPatial Attention Residual Network (SPARNet) built on Face Attention Units (FAUs) for face super-resolution, which effectively extracts key features of facial structures by introducing a spatial attention mechanism. Through quantitative comparisons and the introduction of multi-scale discriminators, the method demonstrates superiority in various metrics and the ability to generate high-resolution images.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Zhenfang Chen, Lin Ma, Wenhan Luo, Kwan-Yee K. Wong
57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019)
(2019)
Meeting Abstract
Gastroenterology & Hepatology
Thomas Ka-Luen Lui, Kwan Yee, Kenneth Wong, Wai Keung Leung
GASTROINTESTINAL ENDOSCOPY
(2019)
Meeting Abstract
Gastroenterology & Hepatology
Thomas Ka-Luen Lui, Kwan Yee, Kenneth Wong, Kwan-Lung Michael Ko, Lung-Yi Mak, Wai Man, Vivien Tsui, Wai Keung Leung
GASTROINTESTINAL ENDOSCOPY
(2019)
Meeting Abstract
Gastroenterology & Hepatology
Thomas Ka-Luen Lui, Kwan Yee, Kenneth Wong, Wai Keung Leung
