Qinfeng Shi

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CSIRO ∙ The University of Adelaide ∙ IEEE

Associate professor, Director of the Probabilistic Graphical Model Group at University of Adelaide

Towards Deep Clustering of Human Activities from Wearables

Our ability to exploit low-cost wearable sensing modalities for critical...
08/02/2020 ∙ by Alireza Abedin, et al. ∙ 0 ∙ share

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Attend And Discriminate: Beyond the State-of-the-Art for Human Activity Recognition using Wearable Sensors

Wearables are fundamental to improving our understanding of human activi...
07/14/2020 ∙ by Alireza Abedin, et al. ∙ 2 ∙ share

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COVID-19 Chest CT Image Segmentation – A Deep Convolutional Neural Network Solution

A novel coronavirus disease 2019 (COVID-19) was detected and has spread ...
04/23/2020 ∙ by Qingsen Yan, et al. ∙ 15 ∙ share

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Learn to Predict Sets Using Feed-Forward Neural Networks

This paper addresses the task of set prediction using deep feed-forward ...
01/30/2020 ∙ by Hamid Rezatofighi, et al. ∙ 30 ∙ share

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Learning to Zoom-in via Learning to Zoom-out: Real-world Super-resolution by Generating and Adapting Degradation

Most learning-based super-resolution (SR) methods aim to recover high-re...
01/08/2020 ∙ by Dong Gong, et al. ∙ 15 ∙ share

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Creating Auxiliary Representations from Charge Definitions for Criminal Charge Prediction

Charge prediction, determining charges for criminal cases by analyzing t...
11/12/2019 ∙ by Liangyi Kang, et al. ∙ 0 ∙ share

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Gradient Information Guided Deraining with A Novel Network and Adversarial Training

In recent years, deep learning based methods have made significant progr...
10/09/2019 ∙ by Yinglong Wang, et al. ∙ 7 ∙ share

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Deep Single Image Deraining Via Estimating Transmission and Atmospheric Light in rainy Scenes

Rain removal in images/videos is still an important task in computer vis...
06/22/2019 ∙ by Yinglong Wang, et al. ∙ 4 ∙ share

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SparseSense: Human Activity Recognition from Highly Sparse Sensor Data-streams Using Set-based Neural Networks

Batteryless or so called passive wearables are providing new and innovat...
06/06/2019 ∙ by Alireza Abedin, et al. ∙ 0 ∙ share

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An Effective Two-Branch Model-Based Deep Network for Single Image Deraining

Removing rain effects from an image automatically has many applications ...
05/14/2019 ∙ by Yinglong Wang, et al. ∙ 6 ∙ share

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Attention-guided Network for Ghost-free High Dynamic Range Imaging

Ghosting artifacts caused by moving objects or misalignments is a key ch...
04/23/2019 ∙ by Qingsen Yan, et al. ∙ 16 ∙ share

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Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis

Generating images via the generative adversarial network (GAN) has attra...
03/27/2019 ∙ by Yong Guo, et al. ∙ 24 ∙ share

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RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion

RGB images differentiate from depth images as they carry more details ab...
03/02/2019 ∙ by Jie Li, et al. ∙ 0 ∙ share

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Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes

As the post-processing step for object detection, non-maximum suppressio...
01/12/2019 ∙ by Yu Liu, et al. ∙ 12 ∙ share

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Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables

Automatic recognition of human activities from time-series sensor data (...
11/20/2018 ∙ by Alireza Abedin Varamin, et al. ∙ 0 ∙ share

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Variational Bayesian Dropout

Variational dropout (VD) is a generalization of Gaussian dropout, which ...
11/19/2018 ∙ by Yuhang Liu, et al. ∙ 0 ∙ share

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MPTV: Matching Pursuit Based Total Variation Minimization for Image Deconvolution

Total variation (TV) regularization has proven effective for a range of ...
10/12/2018 ∙ by Dong Gong, et al. ∙ 0 ∙ share

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Deep Perm-Set Net: Learn to Predict Sets with Unknown Permutation and Cardinality Using Deep Neural Networks

We present a novel approach for learning to predict sets with unknown pe...
05/02/2018 ∙ by S. Hamid Rezatofighi, et al. ∙ 0 ∙ share

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Learning an Optimizer for Image Deconvolution

As an integral component of blind image deblurring, non-blind deconvolut...
04/10/2018 ∙ by Dong Gong, et al. ∙ 0 ∙ share

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Question Answering over Freebase via Attentive RNN with Similarity Matrix based CNN

With the rapid growth of knowledge bases (KBs), question answering over ...
04/10/2018 ∙ by Yingqi Qu, et al. ∙ 0 ∙ share

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Joint Learning of Set Cardinality and State Distribution

We present a novel approach for learning to predict sets using deep lear...
09/13/2017 ∙ by S. Hamid Rezatofighi, et al. ∙ 0 ∙ share

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Beyond Low Rank: A Data-Adaptive Tensor Completion Method

Low rank tensor representation underpins much of recent progress in tens...
08/03/2017 ∙ by Lei Zhang, et al. ∙ 0 ∙ share

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Bayesian Conditional Generative Adverserial Networks

Traditional GANs use a deterministic generator function (typically a neu...
06/17/2017 ∙ by Ehsan Abbasnejad, et al. ∙ 0 ∙ share

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From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blur

Removing pixel-wise heterogeneous motion blur is challenging due to the ...
12/08/2016 ∙ by Dong Gong, et al. ∙ 0 ∙ share

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The Shallow End: Empowering Shallower Deep-Convolutional Networks through Auxiliary Outputs

The depth is one of the key factors behind the great success of convolut...
11/06/2016 ∙ by Yong Guo, et al. ∙ 0 ∙ share

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Image-based Recommendations on Styles and Substitutes

Humans inevitably develop a sense of the relationships between objects, ...
06/15/2015 ∙ by Julian McAuley, et al. ∙ 0 ∙ share

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Hashing on Nonlinear Manifolds

Learning based hashing methods have attracted considerable attention due...
12/02/2014 ∙ by Fumin Shen, et al. ∙ 0 ∙ share

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A Hybrid Loss for Multiclass and Structured Prediction

We propose a novel hybrid loss for multiclass and structured prediction ...
02/09/2014 ∙ by Qinfeng Shi, et al. ∙ 0 ∙ share

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Constraint Reduction using Marginal Polytope Diagrams for MAP LP Relaxations

LP relaxation-based message passing algorithms provide an effective tool...
12/17/2013 ∙ by Zhen Zhang, et al. ∙ 0 ∙ share

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Is margin preserved after random projection?

Random projections have been applied in many machine learning algorithms...
06/18/2012 ∙ by Qinfeng Shi, et al. ∙ 0 ∙ share

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Real-time Visual Tracking Using Sparse Representation

The ℓ_1 tracker obtains robustness by seeking a sparse representation of...
12/12/2010 ∙ by Hanxi Li, et al. ∙ 0 ∙ share

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Qinfeng Shi

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