85 citations · 160 across the 19 of their papers we have counts for
19 papers
Calibrating Uncertainty for Semi-Supervised Crowd Counting
Chen Li, Xiaoling Hu, Shahira Abousamra +1
Semi-supervised crowd counting is an important yet challenging task. A popular approach is to iteratively generate pseudo-labels for unlabeled data and add them to the training set…
Confidence Estimation Using Unlabeled Data
Chen Li, Xiaoling Hu, Chao Chen
Overconfidence is a common issue for deep neural networks, limiting their deployment in real-world applications. To better estimate confidence, existing methods mostly focus on ful…
Topology-Aware Uncertainty for Image Segmentation
Saumya Gupta, Yikai Zhang, Xiaoling Hu +2
Segmentation of curvilinear structures such as vasculature and road networks is challenging due to relatively weak signals and complex geometry/topology. To facilitate and accelera…
Topology-Guided Multi-Class Cell Context Generation for Digital Pathology
Shahira Abousamra, Rajarsi Gupta, Tahsin Kurc +3
In digital pathology, the spatial context of cells is important for cell classification, cancer diagnosis and prognosis. To model such complex cell context, however, is challenging…
Latent Partition Implicit with Surface Codes for 3D Representation
Chao Chen, Yu-Shen Liu, Zhizhong Han
Deep implicit functions have shown remarkable shape modeling ability in various 3D computer vision tasks. One drawback is that it is hard for them to represent a 3D shape as multip…
Learning Topological Interactions for Multi-Class Medical Image Segmentation
Saumya Gupta, Xiaoling Hu, James Kaan +10
Deep learning methods have achieved impressive performance for multi-class medical image segmentation. However, they are limited in their ability to encode topological interactions…