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Found 7 papers, 4 papers with code
Image Deblurring with Domain Generalizable Diffusion Models
Diffusion Probabilistic Models (DPMs) have recently been employed for image deblurring.
Local Spatiotemporal Representation Learning for Longitudinally-consistent Neuroimage Analysis
Recent self-supervised advances in medical computer vision exploit global and local anatomical self-similarity for pretraining prior to downstream tasks such as segmentation.
Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI
Further, such approaches can restrict downstream usage of variably sampled DWIs for usages including the estimation of microstructural indices or tractography.
Generative Adversarial Registration for Improved Conditional Deformable Templates
Deformable templates are essential to large-scale medical image registration, segmentation, and population analysis.
Segmentation-Renormalized Deep Feature Modulation for Unpaired Image Harmonization
Deep networks are now ubiquitous in large-scale multi-center imaging studies.
Structure-Attentioned Memory Network for Monocular Depth Estimation
To this end, we introduce a new Structure-Oriented Memory (SOM) module to learn and memorize the structure-specific information between RGB image domain and the depth domain.
Ranked #27 on
Monocular Depth Estimation
on KITTI Eigen split
3D-A-Nets: 3D Deep Dense Descriptor for Volumetric Shapes with Adversarial Networks
In this paper, powered with a novel design of adversarial networks (3D-A-Nets), we have developed a novel 3D deep dense shape descriptor (3D-DDSD) to address the challenging issues of efficient and effective 3D volumetric data processing.
