activity
20182021
most citedLight Field Spatial Super-resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization

7 citations · 9 across the 6 of their papers we have counts for

collaborators

14 papers

cs.CV20212 cited

Image-based Virtual Fitting Room

Zhiling Huang, Junwen Bu, Jie Chen

Virtual fitting room is a challenging task yet useful feature for e-commerce platforms and fashion designers. Existing works can only detect very few types of fashion items. Beside…

eess.IV2021

Learning Structral coherence Via Generative Adversarial Network for Single Image Super-Resolution

Yuanzhuo Li, Yunan Zheng, Jie Chen +2

Among the major remaining challenges for single image super resolution (SISR) is the capacity to recover coherent images with global shapes and local details conforming to human vi…

eess.IV2020

Edge Adaptive Hybrid Regularization Model For Image Deblurring

Tingting Zhang, Jie Chen, Caiying Wu +3

The parameter selection is crucial to regularization based image restoration methods. Generally speaking, a spatially fixed parameter for regularization item in the whole image doe…

eess.IV2020

Deep Spatial-angular Regularization for Compressive Light Field Reconstruction over Coded Apertures

Mantang Guo, Junhui Hou, Jing Jin +2

Coded aperture is a promising approach for capturing the 4-D light field (LF), in which the 4-D data are compressively modulated into 2-D coded measurements that are further decode…

eess.IV2020

Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual Learning

Zhiyu Zhu, Junhui Hou, Jie Chen +2

This paper explores the problem of hyperspectral image (HSI) super-resolution that merges a low resolution HSI (LR-HSI) and a high resolution multispectral image (HR-MSI). The cros…

cs.CV20207 cited

Light Field Spatial Super-resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization

Jing Jin, Junhui Hou, Jie Chen +1

Light field (LF) images acquired by hand-held devices usually suffer from low spatial resolution as the limited sampling resources have to be shared with the angular dimension. LF…