b'Qinfeng Shi'

research

∙ 08/02/2020

Towards Deep Clustering of Human Activities from Wearables

Our ability to exploit low-cost wearable sensing modalities for critical...

0 Alireza Abedin, et al. ∙

research

∙ 07/14/2020

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...

2 Alireza Abedin, et al. ∙

research

∙ 04/23/2020

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

A novel coronavirus disease 2019 (COVID-19) was detected and has spread ...

15 Qingsen Yan, et al. ∙

research

∙ 01/30/2020

Learn to Predict Sets Using Feed-Forward Neural Networks

This paper addresses the task of set prediction using deep feed-forward ...

30 Hamid Rezatofighi, et al. ∙

research

∙ 01/08/2020

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...

15 Dong Gong, et al. ∙

research

∙ 11/12/2019

Creating Auxiliary Representations from Charge Definitions for Criminal Charge Prediction

Charge prediction, determining charges for criminal cases by analyzing t...

0 Liangyi Kang, et al. ∙

research

∙ 10/09/2019

Gradient Information Guided Deraining with A Novel Network and Adversarial Training

In recent years, deep learning based methods have made significant progr...

7 Yinglong Wang, et al. ∙

research

∙ 06/22/2019

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...

4 Yinglong Wang, et al. ∙

research

∙ 06/06/2019

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...

0 Alireza Abedin, et al. ∙

research

∙ 05/14/2019

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

Removing rain effects from an image automatically has many applications ...

6 Yinglong Wang, et al. ∙

research

∙ 04/23/2019

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

Ghosting artifacts caused by moving objects or misalignments is a key ch...

16 Qingsen Yan, et al. ∙

research

∙ 03/27/2019

Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis

Generating images via the generative adversarial network (GAN) has attra...

24 Yong Guo, et al. ∙

research

∙ 03/02/2019

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

RGB images differentiate from depth images as they carry more details ab...

0 Jie Li, et al. ∙

research

∙ 01/12/2019

Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes

As the post-processing step for object detection, non-maximum suppressio...

12 Yu Liu, et al. ∙

research

∙ 11/20/2018

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

Automatic recognition of human activities from time-series sensor data (...

0 Alireza Abedin Varamin, et al. ∙

research

∙ 11/19/2018

Variational Bayesian Dropout

Variational dropout (VD) is a generalization of Gaussian dropout, which ...

0 Yuhang Liu, et al. ∙

research

∙ 10/12/2018

MPTV: Matching Pursuit Based Total Variation Minimization for Image Deconvolution

Total variation (TV) regularization has proven effective for a range of ...

0 Dong Gong, et al. ∙

research

∙ 05/02/2018

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...

0 S. Hamid Rezatofighi, et al. ∙

research

∙ 04/10/2018

Learning an Optimizer for Image Deconvolution

As an integral component of blind image deblurring, non-blind deconvolut...

0 Dong Gong, et al. ∙

research

∙ 04/10/2018

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

With the rapid growth of knowledge bases (KBs), question answering over ...

0 Yingqi Qu, et al. ∙

research

∙ 09/13/2017

Joint Learning of Set Cardinality and State Distribution

We present a novel approach for learning to predict sets using deep lear...

0 S. Hamid Rezatofighi, et al. ∙

research

∙ 08/03/2017

Beyond Low Rank: A Data-Adaptive Tensor Completion Method

Low rank tensor representation underpins much of recent progress in tens...

0 Lei Zhang, et al. ∙

research

∙ 06/17/2017

Bayesian Conditional Generative Adverserial Networks

Traditional GANs use a deterministic generator function (typically a neu...

0 Ehsan Abbasnejad, et al. ∙

research

∙ 12/08/2016

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 ...

0 Dong Gong, et al. ∙

research

∙ 11/06/2016

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...

0 Yong Guo, et al. ∙

research

∙ 06/15/2015

Image-based Recommendations on Styles and Substitutes

Humans inevitably develop a sense of the relationships between objects, ...

0 Julian McAuley, et al. ∙

research

∙ 12/02/2014

Hashing on Nonlinear Manifolds

Learning based hashing methods have attracted considerable attention due...

0 Fumin Shen, et al. ∙

research

∙ 02/09/2014

A Hybrid Loss for Multiclass and Structured Prediction

We propose a novel hybrid loss for multiclass and structured prediction ...

0 Qinfeng Shi, et al. ∙

research

∙ 12/17/2013

Constraint Reduction using Marginal Polytope Diagrams for MAP LP Relaxations

LP relaxation-based message passing algorithms provide an effective tool...

0 Zhen Zhang, et al. ∙

research

∙ 06/18/2012

Is margin preserved after random projection?

Random projections have been applied in many machine learning algorithms...

0 Qinfeng Shi, et al. ∙

research

∙ 12/12/2010

Real-time Visual Tracking Using Sparse Representation

The ℓ_1 tracker obtains robustness by seeking a sparse representation of...

0 Hanxi Li, et al. ∙

Qinfeng Shi

Featured Co-authors