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20182022
most citedEfficient Trajectory Planning for Multiple Non-holonomic Mobile Robots via Prioritized Trajectory Optimization

106 citations · 127 across the 10 of their papers we have counts for

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8 papers · 1 filter

cs.CV2022

Multiple Degradation and Reconstruction Network for Single Image Denoising via Knowledge Distillation

Juncheng Li, Hanhui Yang, Qiaosi Yi +4

Single image denoising (SID) has achieved significant breakthroughs with the development of deep learning. However, the proposed methods are often accompanied by plenty of paramete…

cs.CV20224 cited

Lightweight Bimodal Network for Single-Image Super-Resolution via Symmetric CNN and Recursive Transformer

Guangwei Gao, Zhengxue Wang, Juncheng Li +3

Single-image super-resolution (SISR) has achieved significant breakthroughs with the development of deep learning. However, these methods are difficult to be applied in real-world…

cs.CV2022

NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results

Longguang Wang, Yulan Guo, Yingqian Wang +3

In this paper, we summarize the 1st NTIRE challenge on stereo image super-resolution (restoration of rich details in a pair of low-resolution stereo images) with a focus on new sol…

cs.CV20211 cited

Efficient and Accurate Multi-scale Topological Network for Single Image Dehazing

Qiaosi Yi, Juncheng Li, Faming Fang +2

Single image dehazing is a challenging ill-posed problem that has drawn significant attention in the last few years. Recently, convolutional neural networks have achieved great suc…

cs.CV20218 cited

Scale-Aware Network with Regional and Semantic Attentions for Crowd Counting under Cluttered Background

Qiaosi Yi, Yunxing Liu, Aiwen Jiang +3

Crowd counting is an important task that shown great application value in public safety-related fields, which has attracted increasing attention in recent years. In the current res…

cs.CV20201 cited

Disentangle Perceptual Learning through Online Contrastive Learning

Kangfu Mei, Yao Lu, Qiaosi Yi +3

Pursuing realistic results according to human visual perception is the central concern in the image transformation tasks. Perceptual learning approaches like perceptual loss are em…