Dong Gong

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Tsinghua University

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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Memorizing Comprehensively to Learn Adaptively: Unsupervised Cross-Domain Person Re-ID with Multi-level Memory

Unsupervised cross-domain person re-identification (Re-ID) aims to adapt...
01/13/2020 ∙ by Xinyu Zhang, et al. ∙ 4 ∙ share

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Semi-supervised Learning via Conditional Rotation Angle Estimation

Self-supervised learning (SlfSL), aiming at learning feature representat...
01/09/2020 ∙ by Hai-Ming Xu, et al. ∙ 38 ∙ 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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Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation

3D point cloud semantic and instance segmentation is crucial and fundame...
01/06/2020 ∙ by Tong He, et al. ∙ 17 ∙ share

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Part-Guided Attention Learning for Vehicle Re-Identification

Vehicle re-identification (Re-ID) often requires one to recognize the fi...
09/13/2019 ∙ by Xinyu Zhang, et al. ∙ 5 ∙ share

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Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation

Training a semantic segmentation model requires a large amount of pixel-...
07/29/2019 ∙ by Tong Shen, et al. ∙ 7 ∙ 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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Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection

Deep autoencoder has been extensively used for anomaly detection. Traini...
04/04/2019 ∙ by Dong Gong, et al. ∙ 34 ∙ share

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Knowledge Adaptation for Efficient Semantic Segmentation

Both accuracy and efficiency are of significant importance to the task o...
03/12/2019 ∙ by Tong He, et al. ∙ 12 ∙ 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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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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End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging

Cardiac magnetic resonance (CMR) is used extensively in the diagnosis an...
10/23/2018 ∙ by Gerard Snaauw, et al. ∙ 4 ∙ 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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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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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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Dong Gong

Featured Co-authors

Chunhua Shen

Lei Zhang

Wei Zhang

Ian Reid

Anton van den Hengel

Jie Yang

Jie Li

Svetha Venkatesh

Yu Liu

Tao Mei

Bo Wang

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

Memorizing Comprehensively to Learn Adaptively: Unsupervised Cross-Domain Person Re-ID with Multi-level Memory

Semi-supervised Learning via Conditional Rotation Angle Estimation

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

Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation

Part-Guided Attention Learning for Vehicle Re-Identification

Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation

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

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

Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection

Knowledge Adaptation for Efficient Semantic Segmentation

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

Variational Bayesian Dropout

End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging

MPTV: Matching Pursuit Based Total Variation Minimization for Image Deconvolution

Learning an Optimizer for Image Deconvolution

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