Search Results for author: Boyun Li

Found 7 papers, 5 papers with code

Comprehensive and Delicate: An Efficient Transformer for Image Restoration

1 code implementation CVPR 2023 Haiyu Zhao, Yuanbiao Gou, Boyun Li, Dezhong Peng, Jiancheng Lv, Xi Peng

Vision Transformers have shown promising performance in image restoration, which usually conduct window- or channel-based attention to avoid intensive computations.

Image Restoration Superpixels

Relationship Quantification of Image Degradations

no code implementations8 Dec 2022 Wenxin Wang, Boyun Li, Yuanbiao Gou, Peng Hu, WangMeng Zuo, Xi Peng

To tackle the first challenge, we proposed a Degradation Relationship Index (DRI) which is defined as the mean drop rate difference in the validation loss between two models which are respectively trained using the anchor degradation and the mixture of the anchor and the auxiliary degradations.

Denoising Image Dehazing +2

All-in-One Image Restoration for Unknown Corruption

1 code implementation CVPR 2022 Boyun Li, Xiao Liu, Peng Hu, Zhongqin Wu, Jiancheng Lv, Xi Peng

In this paper, we study a challenging problem in image restoration, namely, how to develop an all-in-one method that could recover images from a variety of unknown corruption types and levels.

Image Restoration

Unsupervised Neural Rendering for Image Hazing

no code implementations14 Jul 2021 Boyun Li, Yijie Lin, Xiao Liu, Peng Hu, Jiancheng Lv, Xi Peng

To generate plausible haze, we study two less-touched but challenging problems in hazy image rendering, namely, i) how to estimate the transmission map from a single image without auxiliary information, and ii) how to adaptively learn the airlight from exemplars, i. e., unpaired real hazy images.

Image Dehazing Neural Rendering

COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction

1 code implementation CVPR 2021 Yijie Lin, Yuanbiao Gou, Zitao Liu, Boyun Li, Jiancheng Lv, Xi Peng

In this paper, we study two challenging problems in incomplete multi-view clustering analysis, namely, i) how to learn an informative and consistent representation among different views without the help of labels and ii) how to recover the missing views from data.

Clustering Contrastive Learning +2

CLEARER: Multi-Scale Neural Architecture Search for Image Restoration

1 code implementation NeurIPS 2020 Yuanbiao Gou, Boyun Li, Zitao Liu, Songfan Yang, Xi Peng

Different from the existing labor-intensive handcrafted architecture design paradigms, we present a novel method, termed as multi-sCaLe nEural ARchitecture sEarch for image Restoration (CLEARER), which is a specifically designed neural architecture search (NAS) for image restoration.

Image Denoising Image Restoration +2

You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural Network

1 code implementation30 Jun 2020 Boyun Li, Yuanbiao Gou, Shuhang Gu, Jerry Zitao Liu, Joey Tianyi Zhou, Xi Peng

In this paper, we study two challenging and less-touched problems in single image dehazing, namely, how to make deep learning achieve image dehazing without training on the ground-truth clean image (unsupervised) and a image collection (untrained).

Disentanglement Image Dehazing +1

Cannot find the paper you are looking for? You can Submit a new open access paper.