Search Results for author: Trac D. Tran

Found 6 papers, 1 papers with code

Deep filter bank regression for super-resolution of anisotropic MR brain images

no code implementations6 Sep 2022 Samuel W. Remedios, Shuo Han, Yuan Xue, Aaron Carass, Trac D. Tran, Dzung L. Pham, Jerry L. Prince

In 2D multi-slice magnetic resonance (MR) acquisition, the through-plane signals are typically of lower resolution than the in-plane signals.

regression Super-Resolution

Approximate Message Passing with Parameter Estimation for Heavily Quantized Measurements

1 code implementation20 May 2022 Shuai Huang, Deqiang Qiu, Trac D. Tran

In AMP, the signal of interest is assumed to follow certain prior distribution with unknown parameters.


Optical Flow Estimation via Motion Feature Recovery

no code implementations16 Jan 2021 Yang Jiao, Guangming Shi, Trac D. Tran

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.

Optical Flow Estimation

EffiScene: Efficient Per-Pixel Rigidity Inference for Unsupervised Joint Learning of Optical Flow, Depth, Camera Pose and Motion Segmentation

no code implementations CVPR 2021 Yang Jiao, Trac D. Tran, Guangming Shi

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 $\textbf{S}$.

Depth Estimation Motion Segmentation +3

2D+3D Facial Expression Recognition via Discriminative Dynamic Range Enhancement and Multi-Scale Learning

no code implementations16 Nov 2020 Yang Jiao, Yi Niu, Trac D. Tran, Guangming Shi

In 2D+3D facial expression recognition (FER), existing methods generate multi-view geometry maps to enhance the depth feature representation.

3D Facial Expression Recognition

Bayesian Massive MIMO Channel Estimation with Parameter Estimation Using Low-Resolution ADCs

no code implementations29 Jul 2020 Shuai Huang, Deqiang Qiu, Trac D. Tran

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

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