Xiaojuan Qi

Publications113
h-index31
Citations11,030
Highly Influential Citations1,639
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Pyramid Scene Parsing Network
TLDR
This paper exploits the capability of global context information by different-region-based context aggregation through the pyramid pooling module together with the proposed pyramid scene parsing network (PSPNet) to produce good quality results on the scene parsing task.
View on IEEE
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
TLDR
An image cascade network (ICNet) that incorporates multi-resolution branches under proper label guidance to address the challenging task of real-time semantic segmentation is proposed and in-depth analysis of the framework is provided.
View PDF on arXiv
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes
TLDR
This work proposes a novel hybrid densely connected UNet (H-DenseUNet), which consists of a 2-D Dense UNet for efficiently extracting intra-slice features and a 3-D counterpart for hierarchically aggregating volumetric contexts under the spirit of the auto-context algorithm for liver and tumor segmentation.
View on IEEE
The Liver Tumor Segmentation Benchmark (LiTS)
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LITS) organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2016 and…
View PDF on arXiv
DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation
TLDR
An efficient deep contour-aware network (DCAN) to solve this challenging problem under a unified multi-task learning framework and can be efficient when applied to large-scale histopathological data without resorting to additional steps to generate contours based on low-level cues for post-separating.
View on IEEE
Gland segmentation in colon histology images: The glas challenge contest
View on Wolters Kluwer
Image Inpainting via Generative Multi-column Convolutional Neural Networks
TLDR
A generative multi-column network that synthesizes different image components in a parallel manner within one stage to better characterize global structures while an implicit diversified MRF regularization is adopted to enhance local details.
View PDF on arXiv
GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation
TLDR
The proposed Geometric Neural Network (GeoNet) to jointly predict depth and surface normal maps from a single image achieves top performance on surface normal estimation and is on par with state-of-the-art depth estimation methods.
View on IEEE
Semi-Parametric Image Synthesis
TLDR
A semi-parametric approach to photographic image synthesis from semantic layouts that combines the complementary strengths of parametric and nonparametric techniques is presented.
View on IEEE
Deep Contextual Networks for Neuronal Structure Segmentation
TLDR
A deep contextual network is proposed here by leveraging multi-level contextual information from the deep hierarchical structure to achieve better segmentation performance and can potentially facilitate the automatic connectome analysis from EM images with less human intervention effort.
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