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pro vyhledávání: '"Liu Xianpeng"'
Autor:
Liu, Xianpeng, Zheng, Ce, Qian, Ming, Xue, Nan, Chen, Chen, Zhang, Zhebin, Li, Chen, Wu, Tianfu
We present Multi-View Attentive Contextualization (MvACon), a simple yet effective method for improving 2D-to-3D feature lifting in query-based multi-view 3D (MV3D) object detection. Despite remarkable progress witnessed in the field of query-based M
Externí odkaz:
http://arxiv.org/abs/2405.12200
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Pile foundation structures are widely used in the construction of high-piled wharves in coastal soft soil areas due to their excellent adaptability to such environments. However, the extensive, deep backfilling involved in constructing these
Externí odkaz:
https://doaj.org/article/16ce9dcc47554829a0ea3e031aea87e5
The main challenge of monocular 3D object detection is the accurate localization of 3D center. Motivated by a new and strong observation that this challenge can be remedied by a 3D-space local-grid search scheme in an ideal case, we propose a stage-w
Externí odkaz:
http://arxiv.org/abs/2304.01289
Human mesh recovery (HMR) provides rich human body information for various real-world applications. While image-based HMR methods have achieved impressive results, they often struggle to recover humans in dynamic scenarios, leading to temporal incons
Externí odkaz:
http://arxiv.org/abs/2303.13397
Transformer architectures have achieved SOTA performance on the human mesh recovery (HMR) from monocular images. However, the performance gain has come at the cost of substantial memory and computational overhead. A lightweight and efficient model to
Externí odkaz:
http://arxiv.org/abs/2303.13357
Publikováno v:
Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2022)
Monocular 3D object detection aims to localize 3D bounding boxes in an input single 2D image. It is a highly challenging problem and remains open, especially when no extra information (e.g., depth, lidar and/or multi-frames) can be leveraged in train
Externí odkaz:
http://arxiv.org/abs/2112.04628
Many computer scientists use the aggregated answers of online workers to represent ground truth. Prior work has shown that aggregation methods such as majority voting are effective for measuring relatively objective features. For subjective features
Externí odkaz:
http://arxiv.org/abs/2101.04615
Akademický článek
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Akademický článek
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Autor:
Akbarpour, Mahzad, Wu, Qiang, Liu, Xianpeng, Sun, Haiying, Lecuona, Emilia, Tomic, Rade, Bhorade, Sangeeta, Mohanakumar, Thalachallour, Bharat, Ankit
Publikováno v:
In Human Immunology August 2019 80(8):595-601