Search Results for author: Zhiyang Liu

Found 8 papers, 3 papers with code

DR-Pose: A Two-stage Deformation-and-Registration Pipeline for Category-level 6D Object Pose Estimation

1 code implementation5 Sep 2023 Lei Zhou, Zhiyang Liu, Runze Gan, Haozhe Wang, Marcelo H. Ang Jr

In the second stage, a novel registration network is designed to extract pose-sensitive features and predict the representation of object partial point cloud in canonical space based on the deformation results from the first stage.

6D Pose Estimation using RGB Object +1

PEGG-Net: Pixel-Wise Efficient Grasp Generation in Complex Scenes

1 code implementation30 Mar 2022 Haozhe Wang, Zhiyang Liu, Lei Zhou, Huan Yin, Marcelo H Ang Jr

Vision-based grasp estimation is an essential part of robotic manipulation tasks in the real world.

Grasp Generation

Automated Segmentation of Brain Gray Matter Nuclei on Quantitative Susceptibility Mapping Using Deep Convolutional Neural Network

no code implementations3 Aug 2020 Chao Chai, Pengchong Qiao, Bin Zhao, Huiying Wang, Guohua Liu, Hong Wu, E Mark Haacke, Wen Shen, Chen Cao, Xinchen Ye, Zhiyang Liu, Shuang Xia

Abnormal iron accumulation in the brain subcortical nuclei has been reported to be correlated to various neurodegenerative diseases, which can be measured through the magnetic susceptibility from the quantitative susceptibility mapping (QSM).

Fast and Accurate Optical Fiber Channel Modeling Using Generative Adversarial Network

no code implementations28 Feb 2020 Hang Yang, Zekun Niu, Shilin Xiao, Jiafei Fang, Zhiyang Liu, David Faninsin, Lilin Yi

In this work, a new data-driven fiber channel modeling method, generative adversarial network (GAN) is investigated to learn the distribution of fiber channel transfer function.

Generative Adversarial Network

Automatic acute ischemic stroke lesion segmentation using semi-supervised learning

no code implementations10 Aug 2019 Bin Zhao, Shuxue Ding, Hong Wu, Guohua Liu, Chen Cao, Song Jin, Zhiyang Liu

By using a large number of weakly labeled subjects and a small number of fully labeled subjects, our proposed method is able to accurately detect and segment the AIS lesions.

Clustering Ischemic Stroke Lesion Segmentation +1

Cannot find the paper you are looking for? You can Submit a new open access paper.