most citedPC-GAIN: Pseudo-label Conditional Generative Adversarial Imputation Networks for Incomplete Data

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2022

Improve Deep Image Inpainting by Emphasizing the Complexity of Missing Regions

Yufeng Wang, Dan Li, Cong Xu +1

Deep image inpainting research mainly focuses on constructing various neural network architectures or imposing novel optimization objectives. However, on the one hand, building a s…

cs.LG2020★ 2 cited

PC-GAIN: Pseudo-label Conditional Generative Adversarial Imputation Networks for Incomplete Data

Yufeng Wang, Dan Li, Xiang Li +1

Datasets with missing values are very common in real world applications. GAIN, a recently proposed deep generative model for missing data imputation, has been proved to outperform…