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Found 6 papers, 1 papers with code
Deep filter bank regression for super-resolution of anisotropic MR brain images
In 2D multi-slice magnetic resonance (MR) acquisition, the through-plane signals are typically of lower resolution than the in-plane signals.
Approximate Message Passing with Parameter Estimation for Heavily Quantized Measurements
In AMP, the signal of interest is assumed to follow certain prior distribution with unknown parameters.
Optical Flow Estimation via Motion Feature Recovery
In this paper, we discover that the lost information is related to a large quantity of motion features (more than 40%) computed from the popular discriminative cost-volume feature would completely vanish due to invalid sampling, leading to the low efficiency of optical flow learning.
EffiScene: Efficient Per-Pixel Rigidity Inference for Unsupervised Joint Learning of Optical Flow, Depth, Camera Pose and Motion Segmentation
This paper addresses the challenging unsupervised scene flow estimation problem by jointly learning four low-level vision sub-tasks: optical flow $\textbf{F}$, stereo-depth $\textbf{D}$, camera pose $\textbf{P}$ and motion segmentation $\textbf{S}$.
2D+3D Facial Expression Recognition via Discriminative Dynamic Range Enhancement and Multi-Scale Learning
In 2D+3D facial expression recognition (FER), existing methods generate multi-view geometry maps to enhance the depth feature representation.
Bayesian Massive MIMO Channel Estimation with Parameter Estimation Using Low-Resolution ADCs
The proposed approach leads to a much simpler parameter estimation method, allowing us to work with the quantization noise model directly.
Quantization
Information Theory
Signal Processing
Information Theory
