activity
20182022
most citedWeakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images

185 citations · 276 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2022★ 1 cited

Region Proposal Rectification Towards Robust Instance Segmentation of Biological Images

Qilong Zhangli, Jingru Yi, Di Liu +10

Top-down instance segmentation framework has shown its superiority in object detection compared to the bottom-up framework. While it is efficient in addressing over-segmentation, t…

cs.MM2021★ 9 cited

Cross-modal Variational Auto-encoder for Content-based Micro-video Background Music Recommendation

Jing Yi, Yaochen Zhu, Jiayi Xie +1

In this paper, we propose a cross-modal variational auto-encoder (CMVAE) for content-based micro-video background music recommendation. CMVAE is a hierarchical Bayesian generative…

cs.CV2021★ 19 cited

Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images

Jingru Yi, Pengxiang Wu, Hui Tang +7

Instance segmentation is of great importance for many biological applications, such as study of neural cell interactions, plant phenotyping, and quantitatively measuring how cells…

cs.CV2020★ 9 cited

Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors

Jingru Yi, Pengxiang Wu, Bo Liu +3

Oriented object detection in aerial images is a challenging task as the objects in aerial images are displayed in arbitrary directions and are usually densely packed. Current orien…

eess.IV2020

Enhanced MRI Reconstruction Network using Neural Architecture Search

Qiaoying Huang, Dong Yang, Yikun Xian +4

The accurate reconstruction of under-sampled magnetic resonance imaging (MRI) data using modern deep learning technology, requires significant effort to design the necessary comple…

cs.CV2020★ 22 cited

PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data

Meng Ye, Qiaoying Huang, Dong Yang +4

The 3D volumetric shape of the heart's left ventricle (LV) myocardium (MYO) wall provides important information for diagnosis of cardiac disease and invasive procedure navigation.…

cs.CV2020★ 185 cited

Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images

Hui Qu, Pengxiang Wu, Qiaoying Huang +7

Nuclei segmentation is a fundamental task in histopathology image analysis. Typically, such segmentation tasks require significant effort to manually generate accurate pixel-wise a…

eess.IV2020★ 10 cited

Vertebra-Focused Landmark Detection for Scoliosis Assessment

Jingru Yi, Pengxiang Wu, Qiaoying Huang +2

Adolescent idiopathic scoliosis (AIS) is a lifetime disease that arises in children. Accurate estimation of Cobb angles of the scoliosis is essential for clinicians to make diagnos…

cs.CV2019

Point Cloud Processing via Recurrent Set Encoding

Pengxiang Wu, Chao Chen, Jingru Yi +1

We present a new permutation-invariant network for 3D point cloud processing. Our network is composed of a recurrent set encoder and a convolutional feature aggregator. Given an un…

cs.CV2019★ 5 cited

Object-Guided Instance Segmentation for Biological Images

Jingru Yi, Hui Tang, Pengxiang Wu +5

Instance segmentation of biological images is essential for studying object behaviors and properties. The challenges, such as clustering, occlusion, and adhesion problems of the ob…

cs.CV2019★ 1 cited

ASSD: Attentive Single Shot Multibox Detector

Jingru Yi, Pengxiang Wu, Dimitris N. Metaxas

This paper proposes a new deep neural network for object detection. The proposed network, termed ASSD, builds feature relations in the spatial space of the feature map. With the gl…

cs.CV2019★ 9 cited

Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes

Jingru Yi, Pengxiang Wu, Qiaoying Huang +4

Most existing methods handle cell instance segmentation problems directly without relying on additional detection boxes. These methods generally fails to separate touching cells du…

cs.CV2018★ 6 cited

MRI Reconstruction via Cascaded Channel-wise Attention Network

Qiaoying Huang, Dong Yang, Pengxiang Wu +3

We consider an MRI reconstruction problem with input of k-space data at a very low undersampled rate. This can practically benefit patient due to reduced time of MRI scan, but it i…