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20202022
most citedMBA-RainGAN: Multi-branch Attention Generative Adversarial Network for Mixture of Rain Removal from Single Images

7 citations · 11 across the 6 of their papers we have counts for

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7 papers · 1 filter

cs.CV2022

Contrastive Semantic-Guided Image Smoothing Network

Jie Wang, Yongzhen Wang, Yidan Feng +5

Image smoothing is a fundamental low-level vision task that aims to preserve salient structures of an image while removing insignificant details. Deep learning has been explored in…

cs.CV2022

SDA-SNE: Spatial Discontinuity-Aware Surface Normal Estimation via Multi-Directional Dynamic Programming

Nan Ming, Yi Feng, Rui Fan

The state-of-the-art (SoTA) surface normal estimators (SNEs) generally translate depth images into surface normal maps in an end-to-end fashion. Although such SNEs have greatly min…

cs.CV2022

Towards Robust Part-aware Instance Segmentation for Industrial Bin Picking

Yidan Feng, Biqi Yang, Xianzhi Li +7

Industrial bin picking is a challenging task that requires accurate and robust segmentation of individual object instances. Particularly, industrial objects can have irregular shap…

cs.CV2022★ 2 cited

When A Conventional Filter Meets Deep Learning: Basis Composition Learning on Image Filters

Fu Lee Wang, Yidan Feng, Haoran Xie +2

Image filters are fast, lightweight and effective, which make these conventional wisdoms preferable as basic tools in vision tasks. In practical scenarios, users have to tweak para…

cs.CV2021

Adaptive Graph Convolution for Point Cloud Analysis

Haoran Zhou, Yidan Feng, Mingsheng Fang +3

Convolution on 3D point clouds that generalized from 2D grid-like domains is widely researched yet far from perfect. The standard convolution characterises feature correspondences…

cs.CV2021★ 2 cited

Direction-aware Feature-level Frequency Decomposition for Single Image Deraining

Sen Deng, Yidan Feng, Mingqiang Wei +5

We present a novel direction-aware feature-level frequency decomposition network for single image deraining. Compared with existing solutions, the proposed network has three compel…

cs.CV2020★ 7 cited

MBA-RainGAN: Multi-branch Attention Generative Adversarial Network for Mixture of Rain Removal from Single Images

Yiyang Shen, Yidan Feng, Sen Deng +4

Rain severely hampers the visibility of scene objects when images are captured through glass in heavily rainy days. We observe three intriguing phenomenons that, 1) rain is a mixtu…