Search Results for author: Wenming Yang

Found 15 papers, 9 papers with code

Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-based Super-Resolution

no code implementations12 Jan 2022 Bin Xia, Yapeng Tian, Yucheng Hang, Wenming Yang, Qingmin Liao, Jie zhou

To improve matching efficiency, we design a novel Embedded PatchMacth scheme with random samples propagation, which involves end-to-end training with asymptotic linear computational cost to the input size.

Reference-based Super-Resolution

Efficient Non-Local Contrastive Attention for Image Super-Resolution

no code implementations11 Jan 2022 Bin Xia, Yucheng Hang, Yapeng Tian, Wenming Yang, Qingmin Liao, Jie zhou

To demonstrate the effectiveness of ENLCA, we build an architecture called Efficient Non-Local Contrastive Network (ENLCN) by adding a few of our modules in a simple backbone.

Contrastive Learning Image Super-Resolution

ER-IQA: Boosting Perceptual Quality Assessment Using External Reference Images

no code implementations6 May 2021 Jingyu Guo, Wei Wang, Wenming Yang, Qingmin Liao, Jie zhou

In this paper, we introduce a brand new scheme, namely external-reference image quality assessment (ER-IQA), by introducing external reference images to bridge the gap between FR and NR-IQA.

Image Quality Assessment

Attention Cube Network for Image Restoration

1 code implementation13 Sep 2020 Yucheng Hang, Qingmin Liao, Wenming Yang, Yupeng Chen, Jie zhou

The adaptive spatial attention branch (ASAB) and the adaptive channel attention branch (ACAB) constitute the adaptive dual attention module (ADAM), which can capture the long-range spatial and channel-wise contextual information to expand the receptive field and distinguish different types of information for more effective feature representations.

Image Restoration

Real-MFF: A Large Realistic Multi-focus Image Dataset with Ground Truth

no code implementations28 Mar 2020 Juncheng Zhang, Qingmin Liao, Shaojun Liu, Haoyu Ma, Wenming Yang, Jing-Hao Xue

In this letter, we introduce a large and realistic multi-focus dataset called Real-MFF, which contains 710 pairs of source images with corresponding ground truth images.

LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-Resolution

1 code implementation9 Sep 2019 Wenming Yang, Xuechen Zhang, Yapeng Tian, Wei Wang, Jing-Hao Xue, Qingmin Liao

In this paper, we develop a concise but efficient network architecture called linear compressing based skip-connecting network (LCSCNet) for image super-resolution.

Image Super-Resolution

CFSNet: Toward a Controllable Feature Space for Image Restoration

1 code implementation ICCV 2019 Wei Wang, Ruiming Guo, Yapeng Tian, Wenming Yang

Deep learning methods have witnessed the great progress in image restoration with specific metrics (e. g., PSNR, SSIM).

Image Restoration Image Super-Resolution +1

Lightweight Feature Fusion Network for Single Image Super-Resolution

2 code implementations15 Feb 2019 Wenming Yang, Wei Wang, Xuechen Zhang, Shuifa Sun, Qingmin Liao

Specifically, a spindle block is composed of a dimension extension unit, a feature exploration unit and a feature refinement unit.

Image Super-Resolution

Domain-Aware SE Network for Sketch-based Image Retrieval with Multiplicative Euclidean Margin Softmax

1 code implementation11 Dec 2018 Peng Lu, Gao Huang, Hangyu Lin, Wenming Yang, Guodong Guo, Yanwei Fu

This paper proposes a novel approach for Sketch-Based Image Retrieval (SBIR), for which the key is to bridge the gap between sketches and photos in terms of the data representation.

Sketch-Based Image Retrieval

Deep Learning for Single Image Super-Resolution: A Brief Review

1 code implementation9 Aug 2018 Wenming Yang, Xuechen Zhang, Yapeng Tian, Wei Wang, Jing-Hao Xue

Single image super-resolution (SISR) is a notoriously challenging ill-posed problem, which aims to obtain a high-resolution (HR) output from one of its low-resolution (LR) versions.

Image Super-Resolution

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