no code implementations • CVPR 2023 • Rohit Gupta, Anirban Roy, Claire Christensen, Sujeong Kim, Sarah Gerard, Madeline Cincebeaux, Ajay Divakaran, Todd Grindal, Mubarak Shah
We learn a class prototype for each class and a loss function is employed to minimize the distances between a class prototype and the samples from the class.
1 code implementation • 14 Jun 2021 • Xinzi He, Jia Guo, Xuzhe Zhang, Hanwen Bi, Sarah Gerard, David Kaczka, Amin Motahari, Eric Hoffman, Joseph Reinhardt, R. Graham Barr, Elsa Angelini, Andrew Laine
We introduce a recursive refinement network (RRN) for unsupervised medical image registration, to extract multi-scale features, construct normalized local cost correlation volume and recursively refine volumetric deformation vector fields.
Ranked #1 on Image Registration on DIR-LAB COPDgene