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检索条件"机构=NYU Multimedia and Visual Computing Lab"
40 条 记 录,以下是1-10 订阅
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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
来源: 评论
ADAPTIVE WAVELET TRANSFORMER NETWORK FOR 3D SHAPE REPRESENTATION LEARNING  10
ADAPTIVE WAVELET TRANSFORMER NETWORK FOR 3D SHAPE REPRESENTA...
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10th International Conference on Learning Representations, ICLR 2022
作者: Huang, Hao Fang, Yi NYU Multimedia and Visual Computing Lab United States Abu Dhabi United Arab Emirates NYU Tandon School of Engineering New York University United States New York University Abu Dhabi United Arab Emirates
We present a novel method for 3D shape representation learning using multi-scale wavelet decomposition. Previous works often decompose 3D shapes into complementary components in spatial domain at a single scale. In th... 详细信息
来源: 评论
Understanding the Impact of Image Quality and Distance of Objects to Object Detection Performance
Understanding the Impact of Image Quality and Distance of Ob...
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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
作者: Yu Hao Haoyang Pei Yixuan Lyu Zhongzheng Yuan John-Ross Rizzo Yao Wang Yi Fang NYU Multimedia and Visual Computing Lab NYU Tandon and NYU Abu Dhabi NYU Tandon School of Engineering New York University USA NYU Langone Health USA NYUAD Center for Artificial Intelligence and Robotics NYU Abu Dhabi UAE
Object detection is a fundamental task for autonomous driving, which aim to identify and localize objects within an image. Deep learning has made great strides for object detection, with popular models including Faste...
来源: 评论
Understanding the Impact of Image Quality and Distance of Objects to Object Detection Performance
arXiv
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arXiv 2022年
作者: Hao, Yu Pei, Haoyang Lyu, Yixuan Yuan, Zhongzheng Rizzo, John-Ross Wang, Yao Fang, Yi NYU Multimedia and Visual Computing Lab NYU Tandon School of Engineering New York University USA New York University Abu Dhabi UAE NYU Langone Health USA
Deep learning has made great strides for object detection in images, with popular models including Faster R-CNN, YOLO, and SSD. The detection accuracy and computational cost of object detection depend on the spatial r... 详细信息
来源: 评论
3D Unsupervised Region-Aware Registration Transformer
3D Unsupervised Region-Aware Registration Transformer
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IEEE International Conference on Image Processing
作者: Yu Hao Yi Fang NYU Multimedia and Visual Computing Lab New York University Abu Dhabi Abu Dhabi UAE NYUAD Center for Artificial Intelligence and Robotics New York University Abu Dhabi Abu Dhabi UAE
This paper concerns the research problem of point cloud registration to find the rigid transformation to optimally align the source point set with the target one. Learning robust point cloud registration models with d...
来源: 评论
Detect and Approach: Close-Range Navigation Support for People with Blindness and Low Vision
arXiv
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arXiv 2022年
作者: Hao, Yu Feng, Junchi Rizzo, John-Ross Wang, Yao Fang, Yi Nyu Multimedia and Visual Computing Lab Nyu Tandon School of Engineering New York University United States New York University Abu Dhabi United Arab Emirates Nyu Langone Health 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
来源: 评论
3D-MetaConNet: Meta-learning for 3D Shape Classification and Segmentation
3D-MetaConNet: Meta-learning for 3D Shape Classification and...
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International Conference on 3D Imaging, Modeling, Processing, visualization and Transmission (3DIMPVT)
作者: Hao Huang Xiang Li Lingjing Wang Yi Fang NYU Multimedia and Visual Computing Lab USA New York University Abu Dhabi UAE
Supervised learning on 3D shapes are extensively studied by prior literature, among which PointNet [29] and its variants PointNet++ [31] are representatives. However, these methods tackle 3D shape learning problems by... 详细信息
来源: 评论
Meta-Learning 3D Shape Segmentation Functions
arXiv
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arXiv 2021年
作者: Hao, Yu Huang, Hao Yuan, Shuaihang Fang, Yi NYU Multimedia and Visual Computing Lab New York University Abu Dhabi Abu Dhabi United Arab Emirates
Learning robust 3D shape segmentation functions with deep neural networks has emerged as a powerful paradigm, offering promising performance in producing a consistent part segmentation of each 3D shape. Generalizing a... 详细信息
来源: 评论
ROSS: Robust Learning of One-Shot 3D Shape Segmentation
ROSS: Robust Learning of One-Shot 3D Shape Segmentation
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IEEE Workshop on Applications of Computer Vision (WACV)
作者: Shuaihang Yuan Yi Fang NYU Multimedia and Visual Computing Lab USA
3D shape segmentation is a fundamental computer vision task that partitions the object into labeled semantic parts. Recent approaches to 3D shape segmentation learning heavily rely on high-quality labeled training dat... 详细信息
来源: 评论
Pyramid Learnable Tokens for 3D LiDAR Place Recognition
Pyramid Learnable Tokens for 3D LiDAR Place Recognition
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Congcong Wen Hao Huang Yu-Shen Liu Yi Fang NYUAD Center for Artificial Intelligence and Robotics New York University Abu Dhabi UAE NYU Multimedia and Visual Computing Lab New York University USA New York University Abu Dhabi UAE School of Software Tsinghua University Beijing P. R. China
3D LiDAR place recognition plays a vital role in various robot applications' including robotic navigation, autonomous driving, and simultaneous localization and mapping. However, most previous studies evaluated th...
来源: 评论