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Main Authors:	Liu, Shuhong, Bao, Chenyu, Cui, Ziteng, Chu, Xuangeng, Ren, Bin, Gu, Lin, Chen, Xiang, Li, Mingrui, Ma, Long, Conde, Marcos V., Timofte, Radu, Liu, Yun, Umagami, Ryo, Hashimoto, Tomohiro, Hu, Zijian, Gan, Yuan, Xu, Tianhan, Kurose, Yusuke, Harada, Tatsuya, Yuan, Junwei, Chang, Gengjia, Ge, Xining, You, Mache, Cao, Qida, Li, Zeliang, Hu, Xinyuan, Gu, Hongde, Shi, Changyue, Ding, Jiajun, Yu, Zhou, Yu, Jun, Oh, Seungsang, Wang, Fei, Kim, Donggun, Wu, Zhiliang, Ahn, Seho, Zheng, Xinye, Li, Kun, Wei, Yanyan, Lin, Weisi, Zhang, Dizhe, Chen, Yuchao, Song, Meixi, Wang, Hanqing, Feng, Haoran, Qi, Lu, Shan, Jiaao, Gu, Yang, Liu, Jiacheng, Liu, Shiyu, Jiang, Kui, Jiang, Junjun, Zhu, Runyu, Dong, Sixun, Ye, Qingxia, Zhang, Zhiqiang, Xu, Zhihua, Wang, Zhiwei, Son, Phan The, Shi, Zhimiao, Guo, Zixuan, Fu, Xueming, Han, Lixia, Liu, Changhe, Zhao, Zhenyu, Tsukada, Manabu, Zhang, Zheng, Zhai, Zihan, Li, Tingting, Zheng, Ziyang, Liu, Yuhao, Wang, Dingju, You, Jeongbin, Kim, Younghyuk, Kwak, Il-Youp, Lyu, Mingzhe, Yang, Junbo, Yang, Wenhan, Zhang, Hongsen, Cui, Jinqiang, Zhang, Hong, Guo, Haojie, Li, Hantang, Zhu, Qiang, He, Bowen, Meng, Xiandong, Zhao, Debin, Fan, Xiaopeng, Zhou, Wei, Jiang, Linzhe, Li, Linfeng, Xu, Louzhe, Xu, Qi, Song, Hang, Guo, Chenkun, Nie, Weizhi, Li, Yufei, Zhan, Xingan, Shi, Zhanqi, Zhang, Dufeng, Tian, Boyuan, Zeng, Jingshuo, He, Gang, Fu, Yubao, Wang, Weijie, Huang, Cunchuan
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2604.04135
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author	Liu, Shuhong Bao, Chenyu Cui, Ziteng Chu, Xuangeng Ren, Bin Gu, Lin Chen, Xiang Li, Mingrui Ma, Long Conde, Marcos V. Timofte, Radu Liu, Yun Umagami, Ryo Hashimoto, Tomohiro Hu, Zijian Gan, Yuan Xu, Tianhan Kurose, Yusuke Harada, Tatsuya Yuan, Junwei Chang, Gengjia Ge, Xining You, Mache Cao, Qida Li, Zeliang Hu, Xinyuan Gu, Hongde Shi, Changyue Ding, Jiajun Yu, Zhou Yu, Jun Oh, Seungsang Wang, Fei Kim, Donggun Wu, Zhiliang Ahn, Seho Zheng, Xinye Li, Kun Wei, Yanyan Lin, Weisi Zhang, Dizhe Chen, Yuchao Song, Meixi Wang, Hanqing Feng, Haoran Qi, Lu Shan, Jiaao Gu, Yang Liu, Jiacheng Liu, Shiyu Jiang, Kui Jiang, Junjun Zhu, Runyu Dong, Sixun Ye, Qingxia Zhang, Zhiqiang Xu, Zhihua Wang, Zhiwei Son, Phan The Shi, Zhimiao Guo, Zixuan Fu, Xueming Han, Lixia Liu, Changhe Zhao, Zhenyu Tsukada, Manabu Zhang, Zheng Zhai, Zihan Li, Tingting Zheng, Ziyang Liu, Yuhao Wang, Dingju You, Jeongbin Kim, Younghyuk Kwak, Il-Youp Lyu, Mingzhe Yang, Junbo Yang, Wenhan Zhang, Hongsen Cui, Jinqiang Zhang, Hong Guo, Haojie Li, Hantang Zhu, Qiang He, Bowen Meng, Xiandong Zhao, Debin Fan, Xiaopeng Zhou, Wei Jiang, Linzhe Li, Linfeng Xu, Louzhe Xu, Qi Song, Hang Guo, Chenkun Nie, Weizhi Li, Yufei Zhan, Xingan Shi, Zhanqi Zhang, Dufeng Tian, Boyuan Zeng, Jingshuo He, Gang Fu, Yubao Wang, Weijie Huang, Cunchuan
author_facet	Liu, Shuhong Bao, Chenyu Cui, Ziteng Chu, Xuangeng Ren, Bin Gu, Lin Chen, Xiang Li, Mingrui Ma, Long Conde, Marcos V. Timofte, Radu Liu, Yun Umagami, Ryo Hashimoto, Tomohiro Hu, Zijian Gan, Yuan Xu, Tianhan Kurose, Yusuke Harada, Tatsuya Yuan, Junwei Chang, Gengjia Ge, Xining You, Mache Cao, Qida Li, Zeliang Hu, Xinyuan Gu, Hongde Shi, Changyue Ding, Jiajun Yu, Zhou Yu, Jun Oh, Seungsang Wang, Fei Kim, Donggun Wu, Zhiliang Ahn, Seho Zheng, Xinye Li, Kun Wei, Yanyan Lin, Weisi Zhang, Dizhe Chen, Yuchao Song, Meixi Wang, Hanqing Feng, Haoran Qi, Lu Shan, Jiaao Gu, Yang Liu, Jiacheng Liu, Shiyu Jiang, Kui Jiang, Junjun Zhu, Runyu Dong, Sixun Ye, Qingxia Zhang, Zhiqiang Xu, Zhihua Wang, Zhiwei Son, Phan The Shi, Zhimiao Guo, Zixuan Fu, Xueming Han, Lixia Liu, Changhe Zhao, Zhenyu Tsukada, Manabu Zhang, Zheng Zhai, Zihan Li, Tingting Zheng, Ziyang Liu, Yuhao Wang, Dingju You, Jeongbin Kim, Younghyuk Kwak, Il-Youp Lyu, Mingzhe Yang, Junbo Yang, Wenhan Zhang, Hongsen Cui, Jinqiang Zhang, Hong Guo, Haojie Li, Hantang Zhu, Qiang He, Bowen Meng, Xiandong Zhao, Debin Fan, Xiaopeng Zhou, Wei Jiang, Linzhe Li, Linfeng Xu, Louzhe Xu, Qi Song, Hang Guo, Chenkun Nie, Weizhi Li, Yufei Zhan, Xingan Shi, Zhanqi Zhang, Dufeng Tian, Boyuan Zeng, Jingshuo He, Gang Fu, Yubao Wang, Weijie Huang, Cunchuan
contents	This paper presents a comprehensive review of the NTIRE 2026 3D Restoration and Reconstruction (3DRR) Challenge, detailing the proposed methods and results. The challenge seeks to identify robust reconstruction pipelines that are robust under real-world adverse conditions, specifically extreme low-light and smoke-degraded environments, as captured by our RealX3D benchmark. A total of 279 participants registered for the competition, of whom 33 teams submitted valid results. We thoroughly evaluate the submitted approaches against state-of-the-art baselines, revealing significant progress in 3D reconstruction under adverse conditions. Our analysis highlights shared design principles among top-performing methods and provides insights into effective strategies for handling 3D scene degradation.
format	Preprint
id	arxiv_https___arxiv_org_abs_2604_04135
institution	arXiv
publishDate	2026
record_format	arxiv
spellingShingle	NTIRE 2026 3D Restoration and Reconstruction in Real-world Adverse Conditions: RealX3D Challenge Results Liu, Shuhong Bao, Chenyu Cui, Ziteng Chu, Xuangeng Ren, Bin Gu, Lin Chen, Xiang Li, Mingrui Ma, Long Conde, Marcos V. Timofte, Radu Liu, Yun Umagami, Ryo Hashimoto, Tomohiro Hu, Zijian Gan, Yuan Xu, Tianhan Kurose, Yusuke Harada, Tatsuya Yuan, Junwei Chang, Gengjia Ge, Xining You, Mache Cao, Qida Li, Zeliang Hu, Xinyuan Gu, Hongde Shi, Changyue Ding, Jiajun Yu, Zhou Yu, Jun Oh, Seungsang Wang, Fei Kim, Donggun Wu, Zhiliang Ahn, Seho Zheng, Xinye Li, Kun Wei, Yanyan Lin, Weisi Zhang, Dizhe Chen, Yuchao Song, Meixi Wang, Hanqing Feng, Haoran Qi, Lu Shan, Jiaao Gu, Yang Liu, Jiacheng Liu, Shiyu Jiang, Kui Jiang, Junjun Zhu, Runyu Dong, Sixun Ye, Qingxia Zhang, Zhiqiang Xu, Zhihua Wang, Zhiwei Son, Phan The Shi, Zhimiao Guo, Zixuan Fu, Xueming Han, Lixia Liu, Changhe Zhao, Zhenyu Tsukada, Manabu Zhang, Zheng Zhai, Zihan Li, Tingting Zheng, Ziyang Liu, Yuhao Wang, Dingju You, Jeongbin Kim, Younghyuk Kwak, Il-Youp Lyu, Mingzhe Yang, Junbo Yang, Wenhan Zhang, Hongsen Cui, Jinqiang Zhang, Hong Guo, Haojie Li, Hantang Zhu, Qiang He, Bowen Meng, Xiandong Zhao, Debin Fan, Xiaopeng Zhou, Wei Jiang, Linzhe Li, Linfeng Xu, Louzhe Xu, Qi Song, Hang Guo, Chenkun Nie, Weizhi Li, Yufei Zhan, Xingan Shi, Zhanqi Zhang, Dufeng Tian, Boyuan Zeng, Jingshuo He, Gang Fu, Yubao Wang, Weijie Huang, Cunchuan Computer Vision and Pattern Recognition This paper presents a comprehensive review of the NTIRE 2026 3D Restoration and Reconstruction (3DRR) Challenge, detailing the proposed methods and results. The challenge seeks to identify robust reconstruction pipelines that are robust under real-world adverse conditions, specifically extreme low-light and smoke-degraded environments, as captured by our RealX3D benchmark. A total of 279 participants registered for the competition, of whom 33 teams submitted valid results. We thoroughly evaluate the submitted approaches against state-of-the-art baselines, revealing significant progress in 3D reconstruction under adverse conditions. Our analysis highlights shared design principles among top-performing methods and provides insights into effective strategies for handling 3D scene degradation.
title	NTIRE 2026 3D Restoration and Reconstruction in Real-world Adverse Conditions: RealX3D Challenge Results
topic	Computer Vision and Pattern Recognition
url	https://arxiv.org/abs/2604.04135

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