Search Results for author:
Found 5 papers, 4 papers with code
Denoising Distillation Makes Event-Frame Transformers as Accurate Gaze Trackers
Technically, we propose a two-stage learning-based gaze estimation framework to divide the whole gaze estimation process into a coarse-to-fine process of anchor state selection and final gaze location.
Global Structure-Aware Diffusion Process for Low-Light Image Enhancement
To harness the capabilities of diffusion models, we delve into this intricate process and advocate for the regularization of its inherent ODE-trajectory.
Ranked #2 on
Low-Light Image Enhancement
on LOL
Deep Diversity-Enhanced Feature Representation of Hyperspectral Images
In this paper, we study the problem of efficiently and effectively embedding the high-dimensional spatio-spectral information of hyperspectral (HS) images, guided by feature diversity.
Rank-Enhanced Low-Dimensional Convolution Set for Hyperspectral Image Denoising
This paper tackles the challenging problem of hyperspectral (HS) image denoising.
Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolution
Then, we incorporate the proposed feature embedding scheme into a source-consistent super-resolution framework that is physically-interpretable, producing lightweight PDE-Net, in which high-resolution (HR) HS images are iteratively refined from the residuals between input low-resolution (LR) HS images and pseudo-LR-HS images degenerated from reconstructed HR-HS images via probability-inspired HS embedding.
