NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results

no code implementations • 22 Apr 2024 • Xiaoning Liu, Zongwei Wu, Ao Li, Florin-Alexandru Vasluianu, Yulun Zhang, Shuhang Gu, Le Zhang, Ce Zhu, Radu Timofte, Zhi Jin, Hongjun Wu, Chenxi Wang, Haitao Ling, Yuanhao Cai, Hao Bian, Yuxin Zheng, Jing Lin, Alan Yuille, Ben Shao, Jin Guo, Tianli Liu, Mohao Wu, Yixu Feng, Shuo Hou, Haotian Lin, Yu Zhu, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang, Qingsen Yan, Wenbin Zou, Weipeng Yang, Yunxiang Li, Qiaomu Wei, Tian Ye, Sixiang Chen, Zhao Zhang, Suiyi Zhao, Bo wang, Yan Luo, Zhichao Zuo, Mingshen Wang, Junhu Wang, Yanyan Wei, Xiaopeng Sun, Yu Gao, Jiancheng Huang, Hongming Chen, Xiang Chen, Hui Tang, Yuanbin Chen, Yuanbo Zhou, Xinwei Dai, Xintao Qiu, Wei Deng, Qinquan Gao, Tong Tong, Mingjia Li, Jin Hu, Xinyu He, Xiaojie Guo, sabarinathan, K Uma, A Sasithradevi, B Sathya Bama, S. Mohamed Mansoor Roomi, V. Srivatsav, Jinjuan Wang, Long Sun, Qiuying Chen, Jiahong Shao, Yizhi Zhang, Marcos V. Conde, Daniel Feijoo, Juan C. Benito, Alvaro García, Jaeho Lee, Seongwan Kim, Sharif S M A, Nodirkhuja Khujaev, Roman Tsoy, Ali Murtaza, Uswah Khairuddin, Ahmad 'Athif Mohd Faudzi, Sampada Malagi, Amogh Joshi, Nikhil Akalwadi, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudenagudi, Wenyi Lian, Wenjing Lian, Jagadeesh Kalyanshetti, Vijayalaxmi Ashok Aralikatti, Palani Yashaswini, Nitish Upasi, Dikshit Hegde, Ujwala Patil, Sujata C, Xingzhuo Yan, Wei Hao, Minghan Fu, Pooja Choksy, Anjali Sarvaiya, Kishor Upla, Kiran Raja, Hailong Yan, Yunkai Zhang, Baiang Li, Jingyi Zhang, Huan Zheng

This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.

Innovative Quantitative Analysis for Disease Progression Assessment in Familial Cerebral Cavernous Malformations

no code implementations • 23 Mar 2024 • Ruige Zong, Tao Wang, Chunwang Li, Xinlin Zhang, Yuanbin Chen, Longxuan Zhao, Qixuan Li, Qinquan Gao, Dezhi Kang, Fuxin Lin, Tong Tong

To alleviate this problem, we propose a quantitative statistical framework for FCCM, comprising an efficient annotation module, an FCCM lesion segmentation module, and an FCCM lesion quantitative statistics module.

Decision Making Image Registration +1

Wavenumber Domain Sparse Channel Estimation in Holographic MIMO

no code implementations • 17 Mar 2024 • Xufeng Guo, Yuanbin Chen, Ying Wang, Zhaocheng Wang, Zhu Han

In this paper, we investigate the sparse channel estimation in holographic multiple-input multiple-output (HMIMO) systems.

Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image Segmentation

1 code implementation • 17 Nov 2023 • Tao Wang, Yuanbin Chen, Xinlin Zhang, Yuanbo Zhou, Junlin Lan, Bizhe Bai, Tao Tan, Min Du, Qinquan Gao, Tong Tong

Inspired by semi-supervised algorithms that use both labeled and unlabeled data for training, we propose the PLGDF framework, which builds upon the mean teacher network for segmenting medical images with less annotation.

Image Segmentation Pseudo Label +3

Near-Field Sparse Channel Estimation for Extremely Large-Scale RIS-Aided Wireless Communications

no code implementations • 13 Nov 2023 • Zixing Tang, Yuanbin Chen, Ying Wang, Tianqi Mao, Qingqing Wu, Marco Di Renzo, Lajos Hanzo

To tackle this challenge, we exploit the sparsity inherent in the cascaded channel.

Denoising

Dual-Decoder Consistency via Pseudo-Labels Guided Data Augmentation for Semi-Supervised Medical Image Segmentation

1 code implementation • 31 Aug 2023 • Yuanbin Chen, Tao Wang, Hui Tang, Longxuan Zhao, Ruige Zong, Shun Chen, Tao Tan, Xinlin Zhang, Tong Tong

In this paper, we present a novel semi-supervised learning method, Dual-Decoder Consistency via Pseudo-Labels Guided Data Augmentation (DCPA), for medical image segmentation.

Data Augmentation Image Segmentation +3

Location Tracking for Reconfigurable Intelligent Surfaces Aided Vehicle Platoons: Diverse Sparsities Inspired Approaches

no code implementations • 7 May 2023 • Yuanbin Chen, Ying Wang, Xufeng Guo, Zhu Han, Ping Zhang

In this paper, we investigate the employment of reconfigurable intelligent surfaces (RISs) into vehicle platoons, functioning in tandem with a base station (BS) in support of the high-precision location tracking.

Bayesian Inference Philosophy

Reconfigurable Intelligent Surface (RIS)-aided Vehicular Networks: Their Protocols, Resource Allocation, and Performance

no code implementations • 5 Mar 2022 • Yuanbin Chen, Ying Wang, Jiayi Zhang, Ping Zhang, Lajos Hanzo

Reconfigurable intelligent surfaces (RISs) assist in paving the way for the evolution of conventional vehicular networks to autonomous driving.

Autonomous Driving