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Flow-aware synthesis: A generic motion model for video frame interpolation

Computational Visual Media 2021年第3期7卷 393-405页

作者： Jinbo Xing Wenbo Hu Yuechen Zhang Tien-Tsin Wong Department of Computer Science and Engineering the Chinese University of Hong KongHong Kong SARChina Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesChina

A popular and challenging task in video research,frame interpolation aims to increase the frame rate of *** existing methods employ a fixed motion model,e.g.,linear,quadratic,or cubic,to estimate the intermediate warping ***,such fixed motion models cannot well represent the complicated non-linear motions in the real world or rendered ***,we present an adaptive flow prediction module to better approximate the complex motions in ***,interpolating just one intermediate frame between consecutive input frames may be insufficient for complicated non-linear *** enable multi-frame interpolation,we introduce the time as a control variable when interpolating frames between original ones in our generic adaptive flow prediction *** and quantitative experimental results show that our method can produce high-quality results and outperforms the existing stateof-the-art methods on popular public datasets.

关键词： flow-aware generic motion model video frame interpolation

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The Interactive Network Visualization of the interactions Between Topologically Associating Domains in the Genome of Fruit Fly

The Interactive Network Visualization of the Interactions Be...

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17th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2024

作者： Mali, Samira Annavarapu, Swetha Laboratory for Theoretical and Computational Molecular Biophysics Virginia Tech Blacksburg VA United States The Distributed Virtual Environments Lab Center for Human-Computer Interaction Virginia Tech BlacksburgVA United States 3ADP Inc AlpharettaGA United States

In this work, we created a network visualization to help you understand how Topologically Associating Do mains (TADs) interact with each other across the genome based on where the TAD is located, whether it is near the center of the nucleus or near the edge of the nucleus. This visualization can reveal how the dense regions and sparse regions of chromosome interactions are distributed in one view. The pilot study demonstrates how network visualization of TAD-TAD interactions can quickly answer numerous major questions in 3D genome and epigenetics field without requiring the development of Machine Learning methods or Algorithms to un lock Heatmap structures. The questions include but are not limited to, determining many-way interactions and interactions between TADs belonging to various epigenetic classes. © 2024 by SCITEPRESS–Science and Technology Publications, Lda.

关键词： Visualization

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Simulating the Dilution of Sulfuric Acid on Mixed reality Platform 8

Simulating the Dilution of Sulfuric Acid on Mixed Reality Pl...

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8th International Conference on virtual reality, ICVR 2022

作者： Pan, Zhipeng Miao, Jinda Cai, Ning Luo, Tianren Zhang, Mingmin Pan, Zhigeng Research Institute of Virtual Reality and Intelligent Systems Hangzhou Normal University Hangzhou China Zhejiang University College of Computer Science and Technology Hangzhou China Institute of Software Chinese Academy of Sciences State Key Laboratory of Computer Science and Beijing Key Lab of Human-Computer Interaction Beijing China Nanjing University of Information Science and Technology School of Artificial Intelligence Nanjing China

ISBN: (数字)9781665479110

ISBN: (纸本)9781665479110

Augmented reality technology has been widely used in experimental education. Augmented reality provides virtual-real integration, real-Time interaction and three-dimensional immersion, which provides a new development direction for simulating the teaching environment and promoting learning interaction. We have developed an MR experiment of diluting concentrated sulfuric acid, which helps students learn experimental manipulations and scientific concepts before conducting real chemical experiments. virtual experiments can avoid the risks of real chemical experiments and reduce the waste of chemical materials. At the same time, we correctly render the occlusion relationship between the hand, the beaker and the virtual liquid, providing a realistic experimental effect. The tracking of multiple cameras allows students to interact more naturally. We compared the availability and students' attitudes of three virtual experiments about diluting concentrated sulfuric acid. The results show that the usability of the MR experimental system reaches the level of user satisfaction. The realistic visual effects and natural interaction method of the MR experiment have been recognized by the students. © 2022 IEEE.

关键词： Students

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A KALMAN FILTER MODEL FOR SYNCHRONIZATION IN MUSICAL ENSEMBLES

arXiv

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arXiv 2024年

作者： Carvalho, Hugo T. Li, Min S. di Luca, Massimiliano Wing, Alan M. Department of Statistical Methods Federal University of Rio de Janeiro Brazil Bristol Interaction Group School of Computer Science University of Bristol United Kingdom Virtual Reality Lab School of Psychology University of Birmingham United Kingdom

The synchronization of motor responses to rhythmic auditory cues is a fundamental biological phenomenon observed across various species. While the importance of temporal alignment varies across different contexts, achieving precise temporal synchronization is a prominent goal in musical performances. Musicians often incorporate expressive timing variations, which require precise control over timing and synchronization, particularly in ensemble performance. This is crucial because both deliberate expressive nuances and accidental timing deviations can affect the overall timing of a performance. This discussion prompts the question of how musicians adjust their temporal dynamics to achieve synchronization within an ensemble. This paper introduces a novel feedback correction model based on the Kalman Filter, aimed at improving the understanding of interpersonal timing in ensemble music performances. The proposed model performs similarly to other linear correction models in the literature, with the advantage of low computational cost and good performance even in scenarios where the underlying tempo varies. © 2024, CC BY.

关键词： Kalman filters

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Exploiting aliasing for manga restoration

arXiv

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arXiv 2021年

作者： Xie, Minshan Xia, Menghan Wong, Tien-Tsin Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology SIAT CAS

As a popular entertainment art form, manga enriches the line drawings details with bitonal screentones. However, manga resources over the Internet usually show screentone artifacts because of inappropriate scanning/rescaling resolution. In this paper, we propose an innovative twostage method to restore quality bitonal manga from degraded ones. Our key observation is that the aliasing induced by downsampling bitonal screentones can be utilized as informative clues to infer the original resolution and screentones. First, we predict the target resolution from the degraded manga via the Scale Estimation Network (SENet) with spatial voting scheme. Then, at the target resolution, we restore the region-wise bitonal screentones via the Manga Restoration Network (MR-Net) discriminatively, depending on the degradation degree. Specifically, the original screentones are directly restored in pattern-identifiable regions, and visually plausible screentones are synthesized in pattern-agnostic regions. Quantitative evaluation on synthetic data and visual assessment on real-world cases illustrate the effectiveness of our method. Copyright © 2021, The Authors. All rights reserved.

关键词： Restoration

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A New Dynamic Routing Network for Monocular Depth Estimation 12

A New Dynamic Routing Network for Monocular Depth Estimation

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12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022

作者： Luo, Zhehao Luo, Sijin Liang, Guoyuan Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Province Shenzhen China University of Chinese Academy of Sciences Beijing China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences Guangdong Province Shenzhen China Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Province Shenzhen China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Depth estimation is an essential task for understanding the geometry of 3D scenes. Compared with multi-view-based methods, monocular depth estimation is more challenging for the requirement of integrating not only global information but also local cues from various parts. Recently, numerous Convolutional Neural Networks (CNNs) based approaches relying on pre-defined static architectures have been reported. Although many of them have achieved remarkable improvements in accuracy, there remains problem with the generality of the static model when it comes to diverse scenes. In this paper, a novel deep network with dynamic routing architecture is proposed with a dynamically adjustable structure with respect to different inputs, therefore leading to not only improvements on both accuracy and generality but also decrease of the model parameters. Extensive experiments of monocular depth estimation have been conducted on two well-known challenging datasets (i.e., NYUD-v2 and Make3D) as well as the mixed dataset, and have verified the effectiveness of the proposed dynamic framework. © 2022 IEEE.

关键词： Deep neural networks

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Federated semi-supervised medical image classification via inter-client relation matching

arXiv

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arXiv 2021年

作者： Liu, Quande Yang, Hongzheng Dou, Qi Heng, Pheng-Ann Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Department of Computer Science and Engineering Beihang University China Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

Federated learning (FL) has emerged with increasing popularity to collaborate distributed medical institutions for training deep networks. However, despite existing FL algorithms only allow the supervised training setting, most hospitals in realistic usually cannot afford the intricate data labeling due to absence of budget or expertise. This paper studies a practical yet challenging FL problem, named Federated Semi-supervised Learning (FSSL), which aims to learn a federated model by jointly utilizing the data from both labeled and unlabeled clients (i.e., hospitals). We present a novel approach for this problem, which improves over traditional consistency regularization mechanism with a new inter-client relation matching scheme. The proposed learning scheme explicitly connects the learning across labeled and unlabeled clients by aligning their extracted disease relationships, thereby mitigating the deficiency of task knowledge at unlabeled clients and promoting discriminative information from unlabeled samples. We validate our method on two large-scale medical image classification datasets. The effectiveness of our method has been demonstrated with the clear improvements over state-of-the-arts as well as the thorough ablation analysis on both tasks4 © 2021, CC BY-NC-ND.

关键词： Hospitals

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Mixed reality based respiratory liver tumor puncture navigation

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Computational Visual Media 2019年第4期5卷 363-374页

作者： Ruotong Li Weixin Si Xiangyun Liao Qiong Wang Reinhard Klein Pheng-Ann Heng Institute of Computer Science II University of Bonn53115 BonnGermany Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesChina Department of Computer Science and Engineering Chinese University of Hong KongHong KongChina

This paper presents a novel mixed reality based navigation system for accurate respiratory liver tumor punctures in radiofrequency ablation(RFA).Our system contains an optical see-through head-mounted display device(OST-HMD),Microsoft Holo Lens for perfectly overlaying the virtual information on the patient,and a optical tracking system NDI Polaris for calibrating the surgical utilities in the surgical *** with traditional navigation method with CT,our system aligns the virtual guidance information and real patient and real-timely updates the view of virtual guidance via a position tracking *** addition,to alleviate the difficulty during needle placement induced by respiratory motion,we reconstruct the patientspecific respiratory liver motion through statistical motion model to assist doctors precisely puncture liver *** proposed system has been experimentally validated on vivo pigs with an accurate real-time registration approximately 5-mm mean FRE and TRE,which has the potential to be applied in clinical RFA guidance.

关键词： mixed reality human computer interaction statistical motion model

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Difficulty-aware meta-learning for rare disease diagnosis 23rd

Difficulty-aware meta-learning for rare disease diagnosis

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23rd International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2020

作者： Li, Xiaomeng Yu, Lequan Jin, Yueming Fu, Chi-Wing Xing, Lei Heng, Pheng-Ann Department of Computer Science and Engineering The Chinese University of Hong Kong Shatin Hong Kong Department of Radiation Oncology Stanford University Stanford United States Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9783030597092

Rare diseases have extremely low-data regimes, unlike common diseases with large amount of available labeled data. Hence, to train a neural network to classify rare diseases with a few per-class data samples is very challenging, and so far, catches very little attention. In this paper, we present a difficulty-aware meta-learning method to address rare disease classifications and demonstrate its capability to classify dermoscopy images. Our key approach is to first train and construct a meta-learning model from data of common diseases, then adapt the model to perform rare disease classification. To achieve this, we develop the difficulty-aware meta-learning method that dynamically monitors the importance of learning tasks during the meta-optimization stage. To evaluate our method, we use the recent ISIC 2018 skin lesion classification dataset, and show that with only five samples per class, our model can quickly adapt to classify unseen classes by a high AUC of 83.3%. Also, we evaluated several rare disease classification results in the public Dermofit Image Library to demonstrate the potential of our method for real clinical practice. © Springer Nature Switzerland AG 2020.

关键词： Learning systems

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Kine-Appendage: Enhancing Freehand VR interaction through Transformations of virtual Appendages

TechRxiv

引用

TechRxiv 2021年

作者： Bai, Hualong Tian, Yang Zhao, Shengdong Fu, Chi-Wing Wang, Qiong Heng, Pheng-Ann School of Computers Electronics and Information Guangxi University China NUS-HCI Lab National University of Singapore Singapore The Chinese University of Hong Kong China Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology SIAT CAS Shenzhen China

Kinesthetic feedback, the feeling of restriction or resistance when hands contact objects, is essential for natural freehand interaction in VR. However, inducing kinesthetic feedback using mechanical hardware can be cumbersome and difficult in commodity VR systems. We propose a novel approach for providing visual kinesthetic feedback, kine-appendage. It adds a virtual appendage to the user’s avatar hand. During freehand interaction with virtual objects, the appendage exhibits visual transformations, including rotation and deformation, as it makes contact with the surfaces of objects, providing additional feedback to compensate for the loss of kinesthetic feedback in the virtual environment. A proof-of-concept kine-appendage technique, BrittleStylus, was designed to enhance freehand typing. Our empirical evaluation demonstrated that BrittleStylus significantly reduced the uncorrected error rate of naive freehand typing from 6.53% to 1.92% without compromising the typing speed. BrittleStylus also helps to induce a sense of kinesthetic feedback and significantly reduce the possibility of hand penetrating objects. Inspired by the success of BrittleStylus, we further discussed the potential of other kine-appendage techniques. © 2021, CC BY-NC-SA.

关键词： virtual reality

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