6 citations · 6 across the 1 of their papers we have counts for
5 papers
Mask2CAD: 3D Shape Prediction by Learning to Segment and Retrieve
Weicheng Kuo, Anelia Angelova, Tsung-Yi Lin +1
Object recognition has seen significant progress in the image domain, with focus primarily on 2D perception. We propose to leverage existing large-scale datasets of 3D models to un…
ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors
Weicheng Kuo, Anelia Angelova, Jitendra Malik +1
Instance segmentation aims to detect and segment individual objects in a scene. Most existing methods rely on precise mask annotations of every category. However, it is difficult a…
Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection
Weicheng Kuo, Christian Häne, Esther Yuh +2
Deep learning for clinical applications is subject to stringent performance requirements, which raises a need for large labeled datasets. However, the enormous cost of labeling med…
PatchFCN for Intracranial Hemorrhage Detection
Weicheng Kuo, Christian Häne, Esther Yuh +2
This paper studies the problem of detecting and segmenting acute intracranial hemorrhage on head computed tomography (CT) scans. We propose to solve both tasks as a semantic segmen…
From Lifestyle Vlogs to Everyday Interactions
David F. Fouhey, Wei-cheng Kuo, Alexei A. Efros +1
A major stumbling block to progress in understanding basic human interactions, such as getting out of bed or opening a refrigerator, is lack of good training data. Most past effort…