A Theory of Fermat Paths for Non-Line-of-Sight Shape Reconstruction
This paper receive best paper award at #CVPR2019.
Main idea: seeing around the corner at non-line-of-sight (NLOS) objects by using Fermat paths, which is a new theory of how NLOS photons follow specific geometric paths.
Link: http://imaging.cs.cmu.edu/fermat_paths/assets/cvpr2019.pdf
This paper receive best paper award at #CVPR2019.
Main idea: seeing around the corner at non-line-of-sight (NLOS) objects by using Fermat paths, which is a new theory of how NLOS photons follow specific geometric paths.
Link: http://imaging.cs.cmu.edu/fermat_paths/assets/cvpr2019.pdf
Accelerating MRI reconstruction via active acquisition
Researchers from #Facebook AI propose a new approach to MRI reconstruction that restores a high fidelity image from partially observed measurements in less time and with fewer errors.
Link: https://ai.facebook.com/blog/accelerating-mri-reconstruction/
Paper link: https://research.fb.com/publications/reducing-uncertainty-in-undersampled-mri-reconstruction-with-active-acquisition/
#CV #DL #CVPR2019 #healthcare #MRI #biolearning
Researchers from #Facebook AI propose a new approach to MRI reconstruction that restores a high fidelity image from partially observed measurements in less time and with fewer errors.
Link: https://ai.facebook.com/blog/accelerating-mri-reconstruction/
Paper link: https://research.fb.com/publications/reducing-uncertainty-in-undersampled-mri-reconstruction-with-active-acquisition/
#CV #DL #CVPR2019 #healthcare #MRI #biolearning
