activity
20192022
most citedJoint Intensity-Gradient Guided Generative Modeling for Colorization

5 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022

Generative Modeling in Structural-Hankel Domain for Color Image Inpainting

Zihao Li, Chunhua Wu, Shenglin Wu +3

In recent years, some researchers focused on using a single image to obtain a large number of samples through multi-scale features. This study intends to a brand-new idea that requ…

eess.IV2021

Variable Augmented Network for Invertible Modality Synthesis-Fusion

Yuhao Wang, Ruirui Liu, Zihao Li +2

As an effective way to integrate the information contained in multiple medical images under different modalities, medical image synthesis and fusion have emerged in various clinica…

eess.IV20212 cited

High-dimensional Assisted Generative Model for Color Image Restoration

Kai Hong, Chunhua Wu, Cailian Yang +4

This work presents an unsupervised deep learning scheme that exploiting high-dimensional assisted score-based generative model for color image restoration tasks. Considering that t…

cs.CV20205 cited

Joint Intensity-Gradient Guided Generative Modeling for Colorization

Kai Hong, Jin Li, Wanyun Li +4

This paper proposes an iterative generative model for solving the automatic colorization problem. Although previous researches have shown the capability to generate plausible color…

eess.IV20191 cited

Learning Priors in High-frequency Domain for Inverse Imaging Reconstruction

Zhuonan He, Jinjie Zhou, Dong Liang +2

Ill-posed inverse problems in imaging remain an active research topic in several decades, with new approaches constantly emerging. Recognizing that the popular dictionary learning…