16 citations · 19 across the 6 of their papers we have counts for
3 papers · 1 filter
Calibrationless Reconstruction of Uniformly-Undersampled Multi-Channel MR Data with Deep Learning Estimated ESPIRiT Maps
Junhao Zhang, Zheyuan Yi, Yujiao Zhao +8
Purpose: To develop a truly calibrationless reconstruction method that derives ESPIRiT maps from uniformly-undersampled multi-channel MR data by deep learning. Methods: ESPIRiT, on…
UNeRF: Time and Memory Conscious U-Shaped Network for Training Neural Radiance Fields
Abiramy Kuganesan, Shih-yang Su, James J. Little +1
Neural Radiance Fields (NeRFs) increase reconstruction detail for novel view synthesis and scene reconstruction, with applications ranging from large static scenes to dynamic human…
DANBO: Disentangled Articulated Neural Body Representations via Graph Neural Networks
Shih-Yang Su, Timur Bagautdinov, Helge Rhodin
Deep learning greatly improved the realism of animatable human models by learning geometry and appearance from collections of 3D scans, template meshes, and multi-view imagery. Hig…