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With the rapid advancement of generative models, highly realistic image synthesis has posed new challenges to digital security and media credibility. Although AI-generated image detection methods have partially addressed these concerns, a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Chunxiao Li , Xiaoxiao Wang , Meiling Li , Boming Miao , Peng Sun , Yunjian Zhang , Xiangyang Ji , Yao Zhu

In recent years, remarkable advancements have been achieved in the field of image generation, primarily driven by the escalating demand for high-quality outcomes across various image generation subtasks, such as inpainting, denoising, and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Luigi Sigillo , Riccardo Fosco Gramaccioni , Alessandro Nicolosi , Danilo Comminiello

Curb ramps are critical for urban accessibility, but robustly detecting them in images remains an open problem due to the lack of large-scale, high-quality datasets. While prior work has attempted to improve data availability with…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 John S. O'Meara , Jared Hwang , Zeyu Wang , Michael Saugstad , Jon E. Froehlich

Satellite missions provide valuable optical data for monitoring rivers at diverse spatial and temporal scales. However, accessibility remains a challenge: high-resolution imagery is ideal for fine-grained monitoring but is typically scarce…

Image and Video Processing · Electrical Eng. & Systems 2025-11-14 Rangel Daroya , Subhransu Maji

This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the LDV dataset (240 videos) and 95 additional videos. This…

Efficient inspection and accurate diagnosis are required for civil infrastructures with 50 years since completion. Especially in municipalities, the shortage of technical staff and budget constraints on repair expenses have become a…

Computer Vision and Pattern Recognition · Computer Science 2020-05-20 Takato Yasuno , Nakajima Michihiro , Noda Kazuhiro

The detection of flooded areas using high-resolution synthetic aperture radar (SAR) imagery is a critical task with applications in crisis and disaster management, as well as environmental resource planning. However, the complex nature of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Tamer Saleh , Xingxing Weng , Shimaa Holail , Chen Hao , Gui-Song Xia

Automatic security inspection relying on computer vision technology is a challenging task in real-world scenarios due to many factors, such as intra-class variance, class imbalance, and occlusion. Most previous methods rarely touch the…

Computer Vision and Pattern Recognition · Computer Science 2022-11-22 Libo Zhang , Lutao Jiang , Ruyi Ji , Heng Fan

Timely and accurate detection of hurricane debris is critical for effective disaster response and community resilience. While post-disaster aerial imagery is readily available, robust debris segmentation solutions applicable across multiple…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Kooshan Amini , Yuhao Liu , Jamie Ellen Padgett , Guha Balakrishnan , Ashok Veeraraghavan

In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4. This challenge develops…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Yingqian Wang , Longguang Wang , Zhengyu Liang , Jungang Yang , Radu Timofte , Yulan Guo

Salient object detection in complex scenes and environments is a challenging research topic. Most works focus on RGB-based salient object detection, which limits its performance of real-life applications when confronted with adverse…

Computer Vision and Pattern Recognition · Computer Science 2022-05-24 Zhengzheng Tu , Yan Ma , Zhun Li , Chenglong Li , Jieming Xu , Yongtao Liu

This paper presents a comprehensive review of the NTIRE 2026 Low Light Image Enhancement Challenge, highlighting the proposed solutions and final results. The objective of this challenge is to identify effective networks capable of…

Identifying flood affected areas in remote sensing data is a critical problem in earth observation to analyze flood impact and drive responses. While a number of methods have been proposed in the literature, there are two main limitations…

Computer Vision and Pattern Recognition · Computer Science 2024-03-07 Xavier Bou , Thibaud Ehret , Rafael Grompone von Gioi , Jeremy Anger

This study presents the outcomes of the first Controllable Bokeh Rendering Challenge at NTIRE and highlights the most effective submitted methodologies. In total, 44 participants registered for the competition, of which 8 teams submitted…

We introduce the AIM 2025 Real-World RAW Image Denoising Challenge, aiming to advance efficient and effective denoising techniques grounded in data synthesis. The competition is built upon a newly established evaluation benchmark featuring…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Feiran Li , Jiacheng Li , Marcos V. Conde , Beril Besbinar , Vlad Hosu , Daisuke Iso , Radu Timofte

Night Photography Rendering (NPR) poses a significant challenge due to the extreme contrast between dark and illuminated areas in scenes, stemming from concurrent capture of severely dark regions alongside intense point light sources.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Furkan Kınlı

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,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 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

As a pivotal task that bridges remote visual and linguistic understanding, Remote Sensing Image-Text Retrieval (RSITR) has attracted considerable research interest in recent years. However, almost all RSITR methods implicitly assume that…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Qiya Song , Yiqiang Xie , Yuan Sun , Renwei Dian , Xudong Kang

Ireland's coastline, a critical and dynamic resource, is facing challenges such as erosion, sedimentation, and human activities. Monitoring these changes is a complex task we approach using a combination of satellite imagery and deep…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Conor O'Sullivan , Ambrish Kashyap , Seamus Coveney , Xavier Monteys , Soumyabrata Dev

Deploying robust machine learning models has to account for concept drifts arising due to the dynamically changing and non-stationary nature of data. Addressing drifts is particularly imperative in the security domain due to the…

Cryptography and Security · Computer Science 2022-06-16 Aditya Kuppa , Nhien-An Le-Khac
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