Search Results for author: Junchao Zhang

Found 5 papers, 1 papers with code

The PetscSF Scalable Communication Layer

no code implementations25 Feb 2021 Junchao Zhang, Jed Brown, Satish Balay, Jacob Faibussowitsch, Matthew Knepley, Oana Marin, Richard Tran Mills, Todd Munson, Barry F. Smith, Stefano Zampini

PetscSF, the communication component of the Portable, Extensible Toolkit for Scientific Computation (PETSc), is designed to provide PETSc's communication infrastructure suitable for exascale computers that utilize GPUs and other accelerators.

Distributed, Parallel, and Cluster Computing 65F10, 65F50, 68N99, 68W10 G.4; C.2

A Dataset of Human Motion Status Using IR-UWB Through-wall Radar

1 code implementation31 Aug 2020 Zhengliang Zhu, Degui Yang, Junchao Zhang, Feng Tong

Ultra-wideband (UWB) through-wall radar has a wide range of applications in non-contact human information detection and monitoring.

Signal Processing H.4

Weighted Encoding Based Image Interpolation With Nonlocal Linear Regression Model

no code implementations4 Mar 2020 Junchao Zhang

Meanwhile, we incorporate the nonlocal linear regression into this model since nonlocal similar patches could provide a better approximation to a given patch.

Clustering Image Super-Resolution +1

Object-aware Aggregation with Bidirectional Temporal Graph for Video Captioning

no code implementations CVPR 2019 Junchao Zhang, Yuxin Peng

The main novelties and advantages are: (1) Bidirectional temporal graph: A bidirectional temporal graph is constructed along and reversely along the temporal order, which provides complementary ways to capture the temporal trajectories for each salient object.

Video Captioning

Two-stream Collaborative Learning with Spatial-Temporal Attention for Video Classification

no code implementations9 Nov 2017 Yuxin Peng, Yunzhen Zhao, Junchao Zhang

Recently, researchers generally adopt the deep networks to capture the static and motion information \textbf{\emph{separately}}, which mainly has two limitations: (1) Ignoring the coexistence relationship between spatial and temporal attention, while they should be jointly modelled as the spatial and temporal evolutions of video, thus discriminative video features can be extracted.

General Classification Optical Flow Estimation +2

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