Search Results for author: Zehan Zhang

Found 4 papers, 2 papers with code

TopCoW: Benchmarking Topology-Aware Anatomical Segmentation of the Circle of Willis (CoW) for CTA and MRA

1 code implementation • 29 Dec 2023 • Kaiyuan Yang, Fabio Musio, Yihui Ma, Norman Juchler, Johannes C. Paetzold, Rami Al-Maskari, Luciano Höher, Hongwei Bran Li, Ibrahim Ethem Hamamci, Anjany Sekuboyina, Suprosanna Shit, Houjing Huang, Diana Waldmannstetter, Florian Kofler, Fernando Navarro, Martin Menten, Ivan Ezhov, Daniel Rueckert, Iris Vos, Ynte Ruigrok, Birgitta Velthuis, Hugo Kuijf, Julien Hämmerli, Catherine Wurster, Philippe Bijlenga, Laura Westphal, Jeroen Bisschop, Elisa Colombo, Hakim Baazaoui, Andrew Makmur, James Hallinan, Bene Wiestler, Jan S. Kirschke, Roland Wiest, Emmanuel Montagnon, Laurent Letourneau-Guillon, Adrian Galdran, Francesco Galati, Daniele Falcetta, Maria A. Zuluaga, Chaolong Lin, Haoran Zhao, Zehan Zhang, Sinyoung Ra, Jongyun Hwang, HyunJin Park, Junqiang Chen, Marek Wodzinski, Henning Müller, Pengcheng Shi, Wei Liu, Ting Ma, Cansu Yalçin, Rachika E. Hamadache, Joaquim Salvi, Xavier Llado, Uma Maria Lal-Trehan Estrada, Valeriia Abramova, Luca Giancardo, Arnau Oliver, Jialu Liu, Haibin Huang, Yue Cui, Zehang Lin, Yusheng Liu, Shunzhi Zhu, Tatsat R. Patel, Vincent M. Tutino, Maysam Orouskhani, Huayu Wang, Mahmud Mossa-Basha, Chengcheng Zhu, Maximilian R. Rokuss, Yannick Kirchhoff, Nico Disch, Julius Holzschuh, Fabian Isensee, Klaus Maier-Hein, Yuki Sato, Sven Hirsch, Susanne Wegener, Bjoern Menze

The TopCoW dataset was the first public dataset with voxel-level annotations for thirteen possible CoW vessel components, enabled by virtual-reality (VR) technology.

Anatomy Benchmarking +1

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RangeIoUDet: Range Image Based Real-Time 3D Object Detector Optimized by Intersection Over Union

no code implementations • CVPR 2021 • Zhidong Liang, Zehan Zhang, Ming Zhang, Xian Zhao, ShiLiang Pu

Benefiting from the dense representation of the range image, RangeIoUDet is entirely constructed based on 2D convolution, making it possible to have a fast inference speed.

3D Object Detection Autonomous Driving +2

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MAFF-Net: Filter False Positive for 3D Vehicle Detection with Multi-modal Adaptive Feature Fusion

no code implementations • 23 Sep 2020 • Zehan Zhang, Ming Zhang, Zhidong Liang, Xian Zhao, Ming Yang, Wenming Tan, ShiLiang Pu

Experimental results on the KITTI dataset demonstrate significant improvement in filtering false positive over the approach using only point cloud data.

Autonomous Driving

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RangeRCNN: Towards Fast and Accurate 3D Object Detection with Range Image Representation

1 code implementation • 1 Sep 2020 • Zhidong Liang, Ming Zhang, Zehan Zhang, Xian Zhao, ShiLiang Pu

We present RangeRCNN, a novel and effective 3D object detection framework based on the range image representation.

3D Object Detection Data Augmentation +2

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