Search Results for author: Shaohui Liu

Found 23 papers, 18 papers with code

Read Pointer Meters in complex environments based on a Human-like Alignment and Recognition Algorithm

1 code implementation28 Feb 2023 Yan Shu, Shaohui Liu, Honglei Xu, Feng Jiang

Recently, developing an automatic reading system for analog measuring instruments has gained increased attention, as it enables the collection of numerous state of equipment.

Wind Power Scenario Generation Using Graph Convolutional Generative Adversarial Network

no code implementations19 Dec 2022 Young-ho Cho, Shaohui Liu, Duehee Lee, Hao Zhu

Generating wind power scenarios is very important for studying the impacts of multiple wind farms that are interconnected to the grid.

Dynamic Response Recovery Using Ambient Synchrophasor Data: A Synthetic Texas Interconnection Case Study

1 code implementation22 Sep 2022 Shaohui Liu, Hao Zhu, Vassilis Kekatos

Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids.

Fast Hierarchical Deep Unfolding Network for Image Compressed Sensing

no code implementations3 Aug 2022 Wenxue Cui, Shaohui Liu, Debin Zhao

By integrating certain optimization solvers with deep neural network, deep unfolding network (DUN) has attracted much attention in recent years for image compressed sensing (CS).

Image Compressed Sensing

ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild

1 code implementation19 Jul 2022 Wang Zhao, Shaohui Liu, Hengkai Guo, Wenping Wang, Yong-Jin Liu

In addition, our method is able to retain reasonable accuracy of camera poses on fully static scenes, which consistently outperforms strong state-of-the-art dense correspondence based methods with end-to-end deep learning, demonstrating the potential of dense indirect methods based on optical flow and point trajectories.

Motion Segmentation Optical Flow Estimation +1

Topology-aware Graph Neural Networks for Learning Feasible and Adaptive ac-OPF Solutions

1 code implementation16 May 2022 Shaohui Liu, Chengyang Wu, Hao Zhu

We develop a new topology-informed graph neural network (GNN) approach for predicting the optimal solutions of real-time ac-OPF problem.

A Confidence-based Iterative Solver of Depths and Surface Normals for Deep Multi-view Stereo

1 code implementation ICCV 2021 Wang Zhao, Shaohui Liu, Yi Wei, Hengkai Guo, Yong-Jin Liu

Experimental results on ScanNet and RGB-D Scenes V2 demonstrate state-of-the-art performance of the proposed deep MVS system on multi-view depth estimation, with our proposed solver consistently improving the depth quality over both conventional and deep learning based MVS pipelines.

Depth Estimation

Image Compressed Sensing Using Non-local Neural Network

1 code implementation7 Dec 2021 Wenxue Cui, Shaohui Liu, Feng Jiang, Debin Zhao

In this paper, a novel image CS framework using non-local neural network (NL-CSNet) is proposed, which utilizes the non-local self-similarity priors with deep network to improve the reconstruction quality.

Image Compressed Sensing

Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids

1 code implementation4 Oct 2021 Shanny Lin, Shaohui Liu, Hao Zhu

Real-time coordination of distributed energy resources (DERs) is crucial for regulating the voltage profile in distribution grids.

Decision Making

NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo

1 code implementation ICCV 2021 Yi Wei, Shaohui Liu, Yongming Rao, Wang Zhao, Jiwen Lu, Jie zhou

In this work, we present a new multi-view depth estimation method that utilizes both conventional reconstruction and learning-based priors over the recently proposed neural radiance fields (NeRF).

Depth Estimation

Graph Neural Networks for Learning Real-Time Prices in Electricity Market

1 code implementation19 Jun 2021 Shaohui Liu, Chengyang Wu, Hao Zhu

Solving the optimal power flow (OPF) problem in real-time electricity market improves the efficiency and reliability in the integration of low-carbon energy resources into the power grids.

Image Inpainting with Edge-guided Learnable Bidirectional Attention Maps

1 code implementation25 Apr 2021 Dongsheng Wang, Chaohao Xie, Shaohui Liu, Zhenxing Niu, WangMeng Zuo

In this paper, we present an edge-guided learnable bidirectional attention map (Edge-LBAM) for improving image inpainting of irregular holes with several distinct merits.

Image Inpainting

A Dynamic Response Recovery Framework Using Ambient Synchrophasor Data

1 code implementation12 Apr 2021 Shaohui Liu, Hao Zhu, Vassilis Kekatos

Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids.

Multi-Stage Residual Hiding for Image-into-Audio Steganography

no code implementations6 Jan 2021 Wenxue Cui, Shaohui Liu, Feng Jiang, Yongliang Liu, Debin Zhao

The widespread application of audio communication technologies has speeded up audio data flowing across the Internet, which made it a popular carrier for covert communication.

DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracing

1 code implementation CVPR 2020 Shaohui Liu, yinda zhang, Songyou Peng, Boxin Shi, Marc Pollefeys, Zhaopeng Cui

We propose a differentiable sphere tracing algorithm to bridge the gap between inverse graphics methods and the recently proposed deep learning based implicit signed distance function.

Image Inpainting with Learnable Bidirectional Attention Maps

1 code implementation ICCV 2019 Chaohao Xie, Shaohui Liu, Chao Li, Ming-Ming Cheng, WangMeng Zuo, Xiao Liu, Shilei Wen, Errui Ding

Most convolutional network (CNN)-based inpainting methods adopt standard convolution to indistinguishably treat valid pixels and holes, making them limited in handling irregular holes and more likely to generate inpainting results with color discrepancy and blurriness.

Image Inpainting

Normalized Diversification

1 code implementation CVPR 2019 Shaohui Liu, Xiao Zhang, Jianqiao Wangni, Jianbo Shi

We introduce the concept of normalized diversity which force the model to preserve the normalized pairwise distance between the sparse samples from a latent parametric distribution and their corresponding high-dimensional outputs.

Conditional Image Generation Hand Pose Estimation

An Improved Evaluation Framework for Generative Adversarial Networks

1 code implementation20 Mar 2018 Shaohui Liu, Yi Wei, Jiwen Lu, Jie zhou

Unlike most existing evaluation frameworks which transfer the representation of ImageNet inception model to map images onto the feature space, our framework uses a specialized encoder to acquire fine-grained domain-specific representation.

An End-to-End Compression Framework Based on Convolutional Neural Networks

5 code implementations2 Aug 2017 Feng Jiang, Wen Tao, Shaohui Liu, Jie Ren, Xun Guo, Debin Zhao

The second CNN, named reconstruction convolutional neural network (RecCNN), is used to reconstruct the decoded image with high-quality in the decoding end.

Denoising Image Compression

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