Search Results for author: Zhicheng Wang

Found 24 papers, 10 papers with code

Guiding Query Position and Performing Similar Attention for Transformer-Based Detection Heads

no code implementations22 Aug 2021 Xiaohu Jiang, Ze Chen, Zhicheng Wang, Erjin Zhou, ChunYuan

After DETR was proposed, this novel transformer-based detection paradigm which performs several cross-attentions between object queries and feature maps for predictions has subsequently derived a series of transformer-based detection heads.

Adaptive Dilated Convolution For Human Pose Estimation

no code implementations22 Jul 2021 Zhengxiong Luo, Zhicheng Wang, Yan Huang, Liang Wang, Tieniu Tan, Erjin Zhou

It can generate and fuse multi-scale features of the same spatial sizes by setting different dilation rates for different channels.

Pose Estimation

Graph-MLP: Node Classification without Message Passing in Graph

1 code implementation8 Jun 2021 Yang Hu, Haoxuan You, Zhecan Wang, Zhicheng Wang, Erjin Zhou, Yue Gao

Graph Neural Network (GNN) has been demonstrated its effectiveness in dealing with non-Euclidean structural data.

Classification Node Classification

DAVOS: Semi-Supervised Video Object Segmentation via Adversarial Domain Adaptation

no code implementations21 May 2021 Jinshuo Zhang, Zhicheng Wang, Songyan Zhang, Gang Wei

Domain shift has always been one of the primary issues in video object segmentation (VOS), for which models suffer from degeneration when tested on unfamiliar datasets.

Domain Adaptation Semantic Segmentation +2

Physics-informed neural networks (PINNs) for fluid mechanics: A review

no code implementations20 May 2021 Shengze Cai, Zhiping Mao, Zhicheng Wang, Minglang Yin, George Em Karniadakis

Despite the significant progress over the last 50 years in simulating flow problems using numerical discretization of the Navier-Stokes equations (NSE), we still cannot incorporate seamlessly noisy data into existing algorithms, mesh-generation is complex, and we cannot tackle high-dimensional problems governed by parametrized NSE.

TokenPose: Learning Keypoint Tokens for Human Pose Estimation

1 code implementation8 Apr 2021 YanJie Li, Shoukui Zhang, Zhicheng Wang, Sen yang, Wankou Yang, Shu-Tao Xia, Erjin Zhou

Most existing CNN-based methods do well in visual representation, however, lacking in the ability to explicitly learn the constraint relationships between keypoints.

Pose Estimation

V2F-Net: Explicit Decomposition of Occluded Pedestrian Detection

no code implementations7 Apr 2021 Mingyang Shang, Dawei Xiang, Zhicheng Wang, Erjin Zhou

V2F-Net consists of two sub-networks: Visible region Detection Network (VDN) and Full body Estimation Network (FEN).

Pedestrian Detection

Using Low-rank Representation of Abundance Maps and Nonnegative Tensor Factorization for Hyperspectral Nonlinear Unmixing

no code implementations30 Mar 2021 Lianru Gao, Zhicheng Wang, Lina Zhuang, Haoyang Yu, Bing Zhang, Jocelyn Chanussot

Tensor-based methods have been widely studied to attack inverse problems in hyperspectral imaging since a hyperspectral image (HSI) cube can be naturally represented as a third-order tensor, which can perfectly retain the spatial information in the image.

IBRNet: Learning Multi-View Image-Based Rendering

no code implementations CVPR 2021 Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul Srinivasan, Howard Zhou, Jonathan T. Barron, Ricardo Martin-Brualla, Noah Snavely, Thomas Funkhouser

Unlike neural scene representation work that optimizes per-scene functions for rendering, we learn a generic view interpolation function that generalizes to novel scenes.

Neural Rendering Novel View Synthesis

Physics-informed neural networks with hard constraints for inverse design

2 code implementations9 Feb 2021 Lu Lu, Raphael Pestourie, Wenjie Yao, Zhicheng Wang, Francesc Verdugo, Steven G. Johnson

We achieve the same objective as conventional PDE-constrained optimization methods based on adjoint methods and numerical PDE solvers, but find that the design obtained from hPINN is often simpler and smoother for problems whose solution is not unique.

Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation

1 code implementation CVPR 2021 Zhengxiong Luo, Zhicheng Wang, Yan Huang, Tieniu Tan, Erjin Zhou

However, for bottom-up methods, which need to handle a large variance of human scales and labeling ambiguities, the current practice seems unreasonable.

Pose Estimation

Efficient Human Pose Estimation by Learning Deeply Aggregated Representations

no code implementations13 Dec 2020 Zhengxiong Luo, Zhicheng Wang, Yuanhao Cai, GuanAn Wang, Yan Huang, Liang Wang, Erjin Zhou, Tieniu Tan, Jian Sun

Instead, we focus on exploiting multi-scale information from layers with different receptive-field sizes and then making full of use this information by improving the fusion method.

Pose Estimation

EDNet: Efficient Disparity Estimation with Cost Volume Combination and Attention-based Spatial Residual

no code implementations CVPR 2021 Songyan Zhang, Zhicheng Wang, Qiang Wang, Jinshuo Zhang, Gang Wei, Xiaowen Chu

Existing state-of-the-art disparity estimation works mostly leverage the 4D concatenation volume and construct a very deep 3D convolution neural network (CNN) for disparity regression, which is inefficient due to the high memory consumption and slow inference speed.

Disparity Estimation Stereo Matching

A Light-Weight Object Detection Framework with FPA Module for Optical Remote Sensing Imagery

no code implementations7 Sep 2020 Xi Gu, Lingbin Kong, Zhicheng Wang, Jie Li, Zhaohui Yu, Gang Wei

On the DOTA dataset, CenterFPANet mAP is 64. 00%, and FPS is 22. 2, which is close to the accuracy of the anchor-based methods currently used and much faster than them.

Object Detection

High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification

2 code implementations CVPR 2020 Guan'an Wang, Shuo Yang, Huanyu Liu, Zhicheng Wang, Yang Yang, Shuliang Wang, Gang Yu, Erjin Zhou, Jian Sun

When aligning two groups of local features from two images, we view it as a graph matching problem and propose a cross-graph embedded-alignment (CGEA) layer to jointly learn and embed topology information to local features, and straightly predict similarity score.

Graph Matching Person Re-Identification

Learning Delicate Local Representations for Multi-Person Pose Estimation

3 code implementations ECCV 2020 Yuanhao Cai, Zhicheng Wang, Zhengxiong Luo, Binyi Yin, Angang Du, Haoqian Wang, Xiangyu Zhang, Xinyu Zhou, Erjin Zhou, Jian Sun

To tackle this problem, we propose an efficient attention mechanism - Pose Refine Machine (PRM) to make a trade-off between local and global representations in output features and further refine the keypoint locations.

Multi-Person Pose Estimation

Differentiating Features for Scene Segmentation Based on Dedicated Attention Mechanisms

no code implementations19 Nov 2019 Zhiqiang Xiong, Zhicheng Wang, Zhaohui Yu, Xi Gu

In this paper, we differentiate features for scene segmentation based on dedicated attention mechanisms (DF-DAM), and two attention modules are proposed to optimize the high-level and low-level features in the encoder, respectively.

Scene Parsing Scene Segmentation

Deep Learning of Vortex Induced Vibrations

1 code implementation26 Aug 2018 Maziar Raissi, Zhicheng Wang, Michael S. Triantafyllou, George Em. Karniadakis

Of interest is the prediction of the lift and drag forces on the structure given some limited and scattered information on the velocity field.

Cascaded Pyramid Network for Multi-Person Pose Estimation

7 code implementations CVPR 2018 Yilun Chen, Zhicheng Wang, Yuxiang Peng, Zhiqiang Zhang, Gang Yu, Jian Sun

In this paper, we present a novel network structure called Cascaded Pyramid Network (CPN) which targets to relieve the problem from these "hard" keypoints.

Keypoint Detection Multi-Person Pose Estimation

Context-Aware Gaussian Fields for Non-Rigid Point Set Registration

no code implementations CVPR 2016 Gang Wang, Zhicheng Wang, Yufei Chen, Qiangqiang Zhou, Weidong Zhao

Point set registration (PSR) is a fundamental problem in computer vision and pattern recognition, and it has been successfully applied to many applications.

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