Search Results for author: Hong Wu

Found 12 papers, 2 papers with code

End-To-End Audiovisual Feature Fusion for Active Speaker Detection

no code implementations27 Jul 2022 Fiseha B. Tesema, Zheyuan Lin, Shiqiang Zhu, Wei Song, Jason Gu, Hong Wu

After fusion, one BiGRU layer is attached to model the joint temporal dynamics.

Feature Aggregation and Refinement Network for 2D AnatomicalLandmark Detection

1 code implementation1 Nov 2021 Yueyuan Ao, Hong Wu

In this paper, we propose a novel deep network, named feature aggregation and refinement network (FARNet), for the automatic detection of anatomical landmarks.

Full-Resolution Encoder-Decoder Networks with Multi-Scale Feature Fusion for Human Pose Estimation

no code implementations1 Jun 2021 Jie Ou, Mingjian Chen, Hong Wu

To achieve more accurate 2D human pose estimation, we extend the successful encoder-decoder network, simple baseline network (SBN), in three ways.

Pose Estimation Quantization

Efficient Human Pose Estimation with Depthwise Separable Convolution and Person Centroid Guided Joint Grouping

no code implementations6 Dec 2020 Jie Ou, Hong Wu

Two branches of sub-networks are used to predict the centroids, body joints and their offsets to their parent nodes.

Multi-Person Pose Estimation

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).

Hybrid Channel Based Pedestrian Detection

no code implementations28 Dec 2019 Fiseha B. Tesema, Hong Wu, Mingjian Chen, Junpeng Lin, William Zhu, Kai-Zhu Huang

When using a more advanced RPN in our framework, our approach can be further improved and get competitive results on both benchmarks.

Pedestrian Detection

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.

Ischemic Stroke Lesion Segmentation Lesion Segmentation

Training Auto-encoders Effectively via Eliminating Task-irrelevant Input Variables

no code implementations31 May 2016 Hui Shen, Dehua Li, Hong Wu, Zhaoxiang Zang

Auto-encoders are often used as building blocks of deep network classifier to learn feature extractors, but task-irrelevant information in the input data may lead to bad extractors and result in poor generalization performance of the network.

Denoising Variable Selection

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