Zobrazeno 1 - 10
of 97
pro vyhledávání: '"He, Zewei"'
Existing methods attempt to improve models' generalization ability on real-world hazy images by exploring well-designed training schemes (e.g., CycleGAN, prior loss). However, most of them need very complicated training procedures to achieve satisfac
Externí odkaz:
http://arxiv.org/abs/2309.17389
Recently, deep learning-based methods have dominated image dehazing domain. Although very competitive dehazing performance has been achieved with sophisticated models, effective solutions for extracting useful features are still under-explored. In ad
Externí odkaz:
http://arxiv.org/abs/2309.16494
Single image dehazing is a challenging ill-posed problem which estimates latent haze-free images from observed hazy images. Some existing deep learning based methods are devoted to improving the model performance via increasing the depth or width of
Externí odkaz:
http://arxiv.org/abs/2301.04805
Publikováno v:
In Knowledge-Based Systems 27 September 2024 300
Autor:
He, Zewei, He, Sailing
Publikováno v:
In Optics Communications 1 January 2025 574
Publikováno v:
In Optics Communications 15 February 2024 553
Photometric stereo provides an important method for high-fidelity 3D reconstruction based on multiple intensity images captured under different illumination directions. In this paper, we present a complete framework, including a multilight source ill
Externí odkaz:
http://arxiv.org/abs/2012.13720
Autor:
Chen, Du, He, Zewei, Cao, Yanpeng, Yang, Jiangxin, Cao, Yanlong, Yang, Michael Ying, Tang, Siliang, Zhuang, Yueting
Recently, Convolutional Neural Networks (CNNs) have been successfully adopted to solve the ill-posed single image super-resolution (SISR) problem. A commonly used strategy to boost the performance of CNN-based SISR models is deploying very deep netwo
Externí odkaz:
http://arxiv.org/abs/1912.04016
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
He, Zewei, Chen, Du, Cao, Yanpeng, Yang, Jiangxin, Cao, Yanlong, Li, Xin, Tang, Siliang, Zhuang, Yueting, Lu, Zhe-ming
Publikováno v:
In Pattern Recognition January 2023 133