activity
20162020
most citedGeometry Constrained Weakly Supervised Object Localization

9 citations · 29 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2020

Think about boundary: Fusing multi-level boundary information for landmark heatmap regression

Jinheng Xie, Jun Wan, Linlin Shen +1

Although current face alignment algorithms have obtained pretty good performances at predicting the location of facial landmarks, huge challenges remain for faces with severe occlu…

eess.IV20201 cited

MI^2GAN: Generative Adversarial Network for Medical Image Domain Adaptation using Mutual Information Constraint

Xinpeng Xie, Jiawei Chen, Yuexiang Li +3

Domain shift between medical images from multicentres is still an open question for the community, which degrades the generalization performance of deep learning models. Generative…

eess.IV20201 cited

TR-GAN: Topology Ranking GAN with Triplet Loss for Retinal Artery/Vein Classification

Wenting Chen, Shuang Yu, Junde Wu +5

Retinal artery/vein (A/V) classification lays the foundation for the quantitative analysis of retinal vessels, which is associated with potential risks of various cardiovascular an…

cs.CV2020

Translate the Facial Regions You Like Using Region-Wise Normalization

Wenshuang Liu, Wenting Chen, Linlin Shen

Though GAN (Generative Adversarial Networks) based technique has greatly advanced the performance of image synthesis and face translation, only few works available in literature pr…

cs.CV20204 cited

Instance-aware Self-supervised Learning for Nuclei Segmentation

Xinpeng Xie, Jiawei Chen, Yuexiang Li +3

Due to the wide existence and large morphological variances of nuclei, accurate nuclei instance segmentation is still one of the most challenging tasks in computational pathology.…

cs.CV20209 cited

Geometry Constrained Weakly Supervised Object Localization

Weizeng Lu, Xi Jia, Weicheng Xie +3

We propose a geometry constrained network, termed GC-Net, for weakly supervised object localization (WSOL). GC-Net consists of three modules: a detector, a generator and a classifi…