Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Ma, Jianqi"'
Denoising and demosaicking are two fundamental steps in reconstructing a clean full-color video from raw data, while performing video denoising and demosaicking jointly, namely VJDD, could lead to better video restoration performance than performing
Externí odkaz:
http://arxiv.org/abs/2312.16247
Real-world low-resolution (LR) videos have diverse and complex degradations, imposing great challenges on video super-resolution (VSR) algorithms to reproduce their high-resolution (HR) counterparts with high quality. Recently, the diffusion models h
Externí odkaz:
http://arxiv.org/abs/2312.00853
Scene Text Image Super-resolution (STISR) aims to recover high-resolution (HR) scene text images with visually pleasant and readable text content from the given low-resolution (LR) input. Most existing works focus on recovering English texts, which h
Externí odkaz:
http://arxiv.org/abs/2308.03262
The recently developed transformer networks have achieved impressive performance in image denoising by exploiting the self-attention (SA) in images. However, the existing methods mostly use a relatively small window to compute SA due to the quadratic
Externí odkaz:
http://arxiv.org/abs/2302.13598
Scene text image super-resolution aims to increase the resolution and readability of the text in low-resolution images. Though significant improvement has been achieved by deep convolutional neural networks (CNNs), it remains difficult to reconstruct
Externí odkaz:
http://arxiv.org/abs/2203.09388
Publikováno v:
IEEE Conference on Computer Vision and Pattern Recognition 2022
Denoising and demosaicking are two essential steps to reconstruct a clean full-color image from the raw data. Recently, joint denoising and demosaicking (JDD) for burst images, namely JDD-B, has attracted much attention by using multiple raw images c
Externí odkaz:
http://arxiv.org/abs/2203.09294
Autor:
Yu, Haiyang, Chen, Jingye, Li, Bin, Ma, Jianqi, Guan, Mengnan, Xu, Xixi, Wang, Xiaocong, Qu, Shaobo, Xue, Xiangyang
The flourishing blossom of deep learning has witnessed the rapid development of text recognition in recent years. However, the existing text recognition methods are mainly proposed for English texts. As another widely-spoken language, Chinese text re
Externí odkaz:
http://arxiv.org/abs/2112.15093
In the last decade, the blossom of deep learning has witnessed the rapid development of scene text recognition. However, the recognition of low-resolution scene text images remains a challenge. Even though some super-resolution methods have been prop
Externí odkaz:
http://arxiv.org/abs/2112.08171
Scene text image super-resolution (STISR) aims to improve the resolution and visual quality of low-resolution (LR) scene text images, and consequently boost the performance of text recognition. However, most of existing STISR methods regard text imag
Externí odkaz:
http://arxiv.org/abs/2106.15368
Autor:
Guo, Xiaohua, Ma, Jianqi
Publikováno v:
In Journal of Environmental Chemical Engineering February 2024 12(1)
