Search Results for author: Jiahuan Ren

Found 7 papers, 0 papers with code

Clarity ChatGPT: An Interactive and Adaptive Processing System for Image Restoration and Enhancement

no code implementations20 Nov 2023 Yanyan Wei, Zhao Zhang, Jiahuan Ren, Xiaogang Xu, Richang Hong, Yi Yang, Shuicheng Yan, Meng Wang

The generalization capability of existing image restoration and enhancement (IRE) methods is constrained by the limited pre-trained datasets, making it difficult to handle agnostic inputs such as different degradation levels and scenarios beyond their design scopes.

Image Restoration Language Modelling

Seeing Through the Noisy Dark: Towards Real-world Low-Light Image Enhancement and Denoising

no code implementations2 Oct 2022 Jiahuan Ren, Zhao Zhang, Richang Hong, Mingliang Xu, Yi Yang, Shuicheng Yan

Low-light image enhancement (LLIE) aims at improving the illumination and visibility of dark images with lighting noise.

Attribute Denoising +1

Realization of exciton-mediated optical spin-orbit interaction in organic microcrystalline resonators

no code implementations24 Feb 2021 Jiahuan Ren, Qing Liao, Xuekai Ma, Stefan Schumacher, Jiannian Yao, Hongbing Fu

The ability to control the spin-orbit interaction of light in optical microresonators is of fundamental importance for future photonics.

Optics Mesoscale and Nanoscale Physics

Learning Hybrid Representation by Robust Dictionary Learning in Factorized Compressed Space

no code implementations26 Dec 2019 Jiahuan Ren, Zhao Zhang, Sheng Li, Yang Wang, Guangcan Liu, Shuicheng Yan, Meng Wang

Specifically, J-RFDL performs the robust representation by DL in a factorized compressed space to eliminate the negative effects of noise and outliers on the results, which can also make the DL process efficient.

Dictionary Learning

Robust Subspace Discovery by Block-diagonal Adaptive Locality-constrained Representation

no code implementations4 Aug 2019 Zhao Zhang, Jiahuan Ren, Sheng Li, Richang Hong, Zheng-Jun Zha, Meng Wang

Leveraging on the Frobenius-norm based latent low-rank representation model, rBDLR jointly learns the coding coefficients and salient features, and improves the results by enhancing the robustness to outliers and errors in given data, preserving local information of salient features adaptively and ensuring the block-diagonal structures of the coefficients.

Representation Learning

Joint Subspace Recovery and Enhanced Locality Driven Robust Flexible Discriminative Dictionary Learning

no code implementations11 Jun 2019 Zhao Zhang, Jiahuan Ren, Weiming Jiang, Zheng Zhang, Richang Hong, Shuicheng Yan, Meng Wang

We propose a joint subspace recovery and enhanced locality based robust flexible label consistent dictionary learning method called Robust Flexible Discriminative Dictionary Learning (RFDDL).

Dictionary Learning

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