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检索条件"机构=the Multimedia and Visual Computing Lab"
64 条 记 录,以下是31-40 订阅
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An assistive low-vision platform that augments spatial cognition through proprioceptive guidance: Point-to-Tell-and-Touch
An assistive low-vision platform that augments spatial cogni...
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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
作者: Wenjun Gui Bingyu Li Shuaihang Yuan John-Ross Rizzo Lakshay Sharma Chen Feng Anthony Tzes Yi Fang NYU Multimedia and Visual Computing Lab NYU Tandon Langone Medical Center NYU NYU Abu Dhabi NYU Tandon
Spatial cognition, as gained through the sense of vision, is one of the most important capabilities of human beings. However, for the visually impaired (VI), lack of this perceptual capability poses great challenges i...
来源: 评论
Learned binary spectral shape descriptor for 3D shape correspondence
Learned binary spectral shape descriptor for 3D shape corres...
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2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
作者: Xie, Jin Wang, Meng Fang, Yi NYU Multimedia and Visual Computing Lab United Arab Emirates Department of Electrical and Computer Engineering New York University Abu Dhabi United Arab Emirates Department of Electrical and Computer Engineering NYU Tandon School of Engineering United States
Dense 3D shape correspondence is an important problem in computer vision and computer graphics. Recently, the local shape descriptor based 3D shape correspondence approaches have been widely studied, where the local s... 详细信息
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AN INTEGRATED FRAMEWORK FOR DEVELOPING AND EVALUATING AN AUTOMATED LECTURE STYLE ASSESSMENT SYSTEM
arXiv
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arXiv 2023年
作者: Dimitriadou, Eleni Lanitis, Andreas Visual Media Computing Lab Department of Multimedia and Graphic Arts Cyprus University of Technology Limassol Cyprus CYENS Centre of Excellence Nicosia Cyprus
The aim of the work presented in this paper is to develop and evaluate an integrated system that provides automated lecture style evaluation, allowing teachers to get instant feedback related to the goodness of their ... 详细信息
来源: 评论
Detect and Approach: Close-Range Navigation Support for People with Blindness and Low Vision  17th
Detect and Approach: Close-Range Navigation Support for Pe...
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17th European Conference on Computer Vision, ECCV 2022
作者: Hao, Yu Feng, Junchi Rizzo, John-Ross Wang, Yao Fang, Yi NYU Multimedia and Visual Computing Lab New York United States NYU Tandon School of Engineering New York University New York United States New York University Abu Dhabi Abu Dhabi United Arab Emirates NYU Langone Health New York United States
People with blindness and low vision (pBLV) experience significant challenges when locating final destinations or targeting specific objects in unfamiliar environments. Furthermore, besides initially locating and orie... 详细信息
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FairCLIP: Harnessing Fairness in Vision-Language Learning
FairCLIP: Harnessing Fairness in Vision-Language Learning
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Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Yan Luo Min Shi Muhammad Osama Khan Muhammad Muneeb Afzal Hao Huang Shuaihang Yuan Yu Tian Luo Song Ava Kouhana Tobias Elze Yi Fang Mengyu Wang Harvard Ophthalmology AI Lab Harvard University Tandon School of Engineering New York University Multimedia and Visual Computing Lab New York University Abu Dhabi
Fairness is a critical concern in deep learning, especially in healthcare, where these models influence diagnoses and treatment decisions. Although fairness has been investigated in the vision-only domain, the fairnes... 详细信息
来源: 评论
Few-shot Object Detection on Remote Sensing Images
arXiv
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arXiv 2020年
作者: Deng, Jingyu Li, Xiang Fang, Yi Multimedia and Visual Computing Lab NYU Tandon and Abu Dhabi Department of Electrical and Computer Engineering NYU Tandon United States Department of Electrical and Computer Engineering NYU Abu Dhabi United Arab Emirates Multimedia and Visual Computing Lab NYU Tandon and Abu Dhabi Department of Electrical and Computer Engineering Abu Dhabi United Arab Emirates
In this paper, we deal with the problem of object detection on remote sensing images. Previous methods have developed numerous deep CNN-based methods for object detection on remote sensing images and the report remark... 详细信息
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Few-Shot Learning of Part-Specific Probability Space for 3D Shape Segmentation
Few-Shot Learning of Part-Specific Probability Space for 3D ...
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Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Lingjing Wang Xiang Li Yi Fang NYU Multimedia and Visual Computing Lab New York University Abu Dhabi Abu Dhabi UAE New York University New York USA
Recently, deep neural networks are introduced as supervised discriminative models for the learning of 3D point cloud segmentation. Most previous supervised methods require a large number of training data with human an... 详细信息
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Unsupervised Deep Shape Descriptor With Point Distribution Learning
Unsupervised Deep Shape Descriptor With Point Distribution L...
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Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Yi Shi Mengchen Xu Shuaihang Yuan Yi Fang NYU Multimedia and Visual Computing Lab New York University Abu Dhabi Abu Dhabi UAE New York University New York USA
Deep learning models have achieved great success in supervised shape descriptor learning for 3D shape retrieval, classification, and correspondence. However, the unsupervised shape descriptor calculated via deep learn... 详细信息
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3DMotion-Net: Learning Continuous Flow Function for 3D Motion Prediction
arXiv
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arXiv 2020年
作者: Yuan, Shuaihang Li, Xiang Tzes, Anthony Fang, Yi NYU Multimedia and Visual Computing Lab United States New York University Abu Dhabi United Arab Emirates New York University United States
In this paper, we deal with the problem to predict the future 3D motions of 3D object scans from previous two consecutive frames. Previous methods mostly focus on sparse motion prediction in the form of skeletons. Whi... 详细信息
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DeepTracking-Net: 3D Tracking with Unsupervised Learning of Continuous Flow
arXiv
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arXiv 2020年
作者: Yuan, Shuaihang Li, Xiang Fang, Yi NYU Multimedia and Visual Computing Lab United States New York University Abu Dhabi United Arab Emirates New York University United States
This paper deals with the problem of 3D tracking, i.e., to find dense correspondences in a sequence of time-varying 3D shapes. Despite deep learning approaches have achieved promising performance for pairwise dense 3D... 详细信息
来源: 评论