The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report
- URL: http://arxiv.org/abs/2504.10686v1
- Date: Mon, 14 Apr 2025 20:18:21 GMT
- Title: The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report
- Authors: Bin Ren, Hang Guo, Lei Sun, Zongwei Wu, Radu Timofte, Yawei Li, Yao Zhang, Xinning Chai, Zhengxue Cheng, Yingsheng Qin, Yucai Yang, Li Song, Hongyuan Yu, Pufan Xu, Cheng Wan, Zhijuan Huang, Peng Guo, Shuyuan Cui, Chenjun Li, Xuehai Hu, Pan Pan, Xin Zhang, Heng Zhang, Qing Luo, Linyan Jiang, Haibo Lei, Qifang Gao, Yaqing Li, Weihua Luo, Tsing Li, Qing Wang, Yi Liu, Yang Wang, Hongyu An, Liou Zhang, Shijie Zhao, Lianhong Song, Long Sun, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Jing Wei, Mengyang Wang, Ruilong Guo, Qian Wang, Qingliang Liu, Yang Cheng, Davinci, Enxuan Gu, Pinxin Liu, Yongsheng Yu, Hang Hua, Yunlong Tang, Shihao Wang, Yukun Yang, Zhiyu Zhang, Yukun Yang, Jiyu Wu, Jiancheng Huang, Yifan Liu, Yi Huang, Shifeng Chen, Rui Chen, Yi Feng, Mingxi Li, Cailu Wan, Xiangji Wu, Zibin Liu, Jinyang Zhong, Kihwan Yoon, Ganzorig Gankhuyag, Shengyun Zhong, Mingyang Wu, Renjie Li, Yushen Zuo, Zhengzhong Tu, Zongang Gao, Guannan Chen, Yuan Tian, Wenhui Chen, Weijun Yuan, Zhan Li, Yihang Chen, Yifan Deng, Ruting Deng, Yilin Zhang, Huan Zheng, Yanyan Wei, Wenxuan Zhao, Suiyi Zhao, Fei Wang, Kun Li, Yinggan Tang, Mengjie Su, Jae-hyeon Lee, Dong-Hyeop Son, Ui-Jin Choi, Tiancheng Shao, Yuqing Zhang, Mengcheng Ma, Donggeun Ko, Youngsang Kwak, Jiun Lee, Jaehwa Kwak, Yuxuan Jiang, Qiang Zhu, Siyue Teng, Fan Zhang, Shuyuan Zhu, Bing Zeng, David Bull, Jing Hu, Hui Deng, Xuan Zhang, Lin Zhu, Qinrui Fan, Weijian Deng, Junnan Wu, Wenqin Deng, Yuquan Liu, Zhaohong Xu, Jameer Babu Pinjari, Kuldeep Purohit, Zeyu Xiao, Zhuoyuan Li, Surya Vashisth, Akshay Dudhane, Praful Hambarde, Sachin Chaudhary, Satya Naryan Tazi, Prashant Patil, Santosh Kumar Vipparthi, Subrahmanyam Murala, Wei-Chen Shen, I-Hsiang Chen, Yunzhe Xu, Chen Zhao, Zhizhou Chen, Akram Khatami-Rizi, Ahmad Mahmoudi-Aznaveh, Alejandro Merino, Bruno Longarela, Javier Abad, Marcos V. Conde, Simone Bianco, Luca Cogo, Gianmarco Corti,
- Abstract summary: The NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution (ESR) aims to advance the development of models that optimize key computational metrics.<n>This paper meticulously analyzes these methods and results, emphasizing groundbreaking advancements in state-of-the-art single-image ESR techniques.
- Score: 170.81876816944754
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This paper presents a comprehensive review of the NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution (ESR). The challenge aimed to advance the development of deep models that optimize key computational metrics, i.e., runtime, parameters, and FLOPs, while achieving a PSNR of at least 26.90 dB on the $\operatorname{DIV2K\_LSDIR\_valid}$ dataset and 26.99 dB on the $\operatorname{DIV2K\_LSDIR\_test}$ dataset. A robust participation saw \textbf{244} registered entrants, with \textbf{43} teams submitting valid entries. This report meticulously analyzes these methods and results, emphasizing groundbreaking advancements in state-of-the-art single-image ESR techniques. The analysis highlights innovative approaches and establishes benchmarks for future research in the field.
Related papers
- NTIRE 2025 Challenge on Image Super-Resolution ($\times$4): Methods and Results [159.15538432295656]
The NTIRE 2025 image super-resolution ($times$4) challenge is one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025.
The challenge aims to recover high-resolution (HR) images from low-resolution (LR) counterparts generated through bicubic downsampling with a $times$4 scaling factor.
A total of 286 participants registered for the competition, with 25 teams submitting valid entries.
arXiv Detail & Related papers (2025-04-20T12:08:22Z) - NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Results [191.59142290750043]
Cross-Domain Few-Shot Object Detection (CD-FSOD) poses significant challenges to existing object detection models when applied across domains.<n>In conjunction with NTIRE 2025, we organized the 1st CD-FSOD Challenge, aiming to advance the performance of current object detectors on entirely novel target domains with only limited labeled data.<n>We present an overview of the 1st NTIRE 2025 CD-FSOD Challenge, highlighting the proposed solutions and summarizing the results submitted by the participants.
arXiv Detail & Related papers (2025-04-14T20:17:27Z) - The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report [180.94772271910315]
This paper reviews the NTIRE 2024 challenge, focusing on efficient single-image super-resolution (ESR) solutions.
The primary objective is to develop networks that optimize various aspects such as runtime, parameters, and FLOPs.
The challenge had 262 registered participants, and 34 teams made valid submissions.
arXiv Detail & Related papers (2024-04-16T07:26:20Z) - NTIRE 2024 Challenge on Image Super-Resolution ($\times$4): Methods and Results [126.78130602974319]
This paper reviews the NTIRE 2024 challenge on image super-resolution ($times$4)
The challenge involves generating corresponding high-resolution (HR) images, magnified by a factor of four, from low-resolution (LR) inputs.
The aim of the challenge is to obtain designs/solutions with the most advanced SR performance.
arXiv Detail & Related papers (2024-04-15T13:45:48Z) - HAlf-MAsked Model for Named Entity Sentiment analysis [0.0]
We study different transformers-based solutions NESA in RuSentNE-23 evaluation.
We present several approaches to overcome this problem, among which there is a novel technique of additional pass over given data with masked entity.
Our proposed model achieves the best result on RuSentNE-23 evaluation data and demonstrates improved consistency in entity-level sentiment analysis.
arXiv Detail & Related papers (2023-08-30T06:53:24Z) - NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset,
Methods and Results [94.63112105689488]
This report summarizes the first NTIRE challenge on light field (LF) image super-resolution (SR)
It aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4.
We report the solutions proposed by the participants, and summarize their common trends and useful tricks.
arXiv Detail & Related papers (2023-04-20T15:59:31Z) - Controllable Textual Inversion for Personalized Text-to-Image Generation [24.18758951295929]
Text inversion (TI) is proposed as an effective technique in personalizing the generation when the prompts contain user-defined, unseen or long-tail concept tokens.
In this work, we propose a much-enhanced version of TI, dubbed Controllable Textual Inversion (COTI) in resolving all the aforementioned problems and in turn delivering a robust, data-efficient and easy-to-use framework.
arXiv Detail & Related papers (2023-04-11T14:56:44Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.