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检索条件"机构=Computer Vision and Robotics Laboratory"
644 条 记 录,以下是171-180 订阅
排序:
Simultaneous enhancement and super-resolution of underwater imagery for improved visual perception
arXiv
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arXiv 2020年
作者: Islam, Md Jahidul Luo, Peigen Sattar, Junaed Interactive Robotics and Vision Laboratory Department of Computer Science and Engineering Minnesota Robotics Institute University of Minnesota Twin CitiesMN United States
In this paper, we introduce and tackle the simultaneous enhancement and super-resolution (SESR) problem for underwater robot vision and provide an efficient solution for near real-time applications. We present Deep SE... 详细信息
来源: 评论
SurgT challenge: Benchmark of Soft-Tissue Trackers for Robotic Surgery
arXiv
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arXiv 2023年
作者: Cartucho, João Weld, Alistair Tukra, Samyakh Xu, Haozheng Matsuzaki, Hiroki Ishikawa, Taiyo Kwon, Minjun Jang, Yong Eun Kim, Kwang-Ju Lee, Gwang Bai, Bizhe Kahrs, Lueder Boecking, Lars Allmendinger, Simeon Müller, Leopold Zhang, Yitong Jin, Yueming Bano, Sophia Vasconcelos, Francisco Reiter, Wolfgang Hajek, Jonas Silva, Bruno Lima, Estevão Vilaça, João L. Queirós, Sandro Giannarou, Stamatia The Hamlyn Centre for Robotic Surgery Imperial College London United Kingdom Jmees Japan Daejeon Korea Republic of Ajou University Gyeonggi-do Korea Republic of Medical Computer Vision and Robotics Lab University of Toronto Canada Germany Surgical Robot Vision University College London United Kingdom Company Name RIWOlink GmbH Munich Germany School of Medicine University of Minho Braga Portugal ICVS/3B’s - PT Government Associate Laboratory Braga/Guimarães Portugal 2Ai - School of Technology IPCA Barcelos Portugal
This paper introduces the "SurgT: Surgical Tracking" challenge which was organised in conjunction with the 25th International Conference on Medical Image Computing and computer-Assisted Intervention (MICCAI ... 详细信息
来源: 评论
Line Drawing Guided Progressive Inpainting of Mural Damage
arXiv
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arXiv 2022年
作者: Li, Luxi Zou, Qin Zhang, Fan Yu, Hongkai Chen, Long Song, Chengfang Huang, Xianfeng Wang, Xiaoguang Li, Qingquan Department of Computer Science Technology United International College of Beijing Normal University HongKong Baptist University Zhuhai China Machine Vision and Robotics Laboratory School of Computer Science Wuhan University Wuhan China State Key Laboratory of Surveying Mapping and Remote Sensing Information Engineering Wuhan University Wuhan China Department of Electrical Engineering and Computer Science Cleveland State University OH United States Institute of Automation Chinese Academy of Sciences Beijing China Cultural Heritage Intelligent Computing Laboratory Wuhan University Wuhan China Guangming Laboratory Shenzhen University Shenzhen China
Mural image inpainting is far less explored compared to its natural image counterpart and remains largely unsolved. Most existing image-inpainting methods tend to take the target image as the only input and directly r... 详细信息
来源: 评论
Image saliency detection via multi-feature and manifold-space ranking  2021
Image saliency detection via multi-feature and manifold-spac...
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3rd Asia Pacific Information Technology Conference, APIT 2021
作者: Li, Xiaoli Zhao, Huaici Liu, Yunpeng Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Opto-Electronic Information Processing Shenyang110016 China The Key Lab of Image Understanding and Computer Vision Shenyang110016 China Shenyang Jianzhu University Shenyang110168 China
In this paper, we propose an image saliency detection method by using multi-feature and manifold-space ranking. Basically, the proposed method extracts the color-histogram feature to obtain the fine information of the... 详细信息
来源: 评论
An Improved SSD for small target detection
An Improved SSD for small target detection
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作者: Xiang Li Haibo LuoX Key Laboratory of Opt-Electronic Information Processing Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences The Key Laboratory of Image Understanding and Computer Vision
SSD is one of heuristic one-stage target detection *** it has got impressive results in general target detection,it still struggles in small-size object detection and precise *** this paper,we proposed an improved SSD... 详细信息
来源: 评论
RDA: An Accelerated Collision Free Motion Planner for Autonomous Navigation in Cluttered Environments
arXiv
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arXiv 2022年
作者: Han, Ruihua Wang, Shuai Wang, Shuaijun Zhang, Zeqing Zhang, Qianru Eldar, Yonina C. Hao, Qi Pan, Jia The Department of Computer Science and Engineering Southern University of Science and Technology Guangdong Shenzhen China The Department of Computer Science The University of Hong Kong Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China The Department of Computer Science and Engineering Harbin Institute of Technology Guangdong Shenzhen China The Weizmann Institute of Science Rehovot Israel The Department of Computer Science and Engineering The Shenzhen Key Laboratory of Robotics and Computer Vision The Sifakis Research Institute for Trustworthy Autonomous Systems Southern University of Science and Technology Guangdong Shenzhen China
Autonomous motion planning is challenging in multi-obstacle environments due to nonconvex collision avoidance constraints. Directly applying numerical solvers to these nonconvex formulations fails to exploit the const... 详细信息
来源: 评论
NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report
NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report
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2023 IEEE/CVF Conference on computer vision and Pattern Recognition Workshops, CVPRW 2023
作者: Ancuti, Codruta O. Ancuti, Cosmin Vasluianu, Florin-Alexandru Timofte, Radu Zhou, Han Dong, Wei Liu, Yangyi Chen, Jun Liu, Huan Li, Liangyan Wu, Zijun Dong, Yubo Li, Yuyan Qiu, Tian He, Yu Lu, Yonghong Wu, Yinwei Jiang, Zhenxiang Liu, Songhua Yang, Xingyi Jing, Yongcheng Benjdira, Bilel Ali, Anas M. Koubaa, Anis Yang, Hao-Hsiang Chen, I-Hsiang Chen, Wei-Ting Huang, Zhi-Kai Chen, Yi-Chung Hsieh, Chia-Hsuan Chang, Hua-En Chiang, Yuan-Chun Kuo, Sy-Yen Guo, Yu Gao, Yuan Liu, Ryan Wen Lu, Yuxu Qu, Jingxiang He, Shengfeng Ren, Wenqi Hoang, Trung Zhang, Haichuan Yazdani, Amirsaeed Monga, Vishal Yang, Lehan Wu, Alex Jiahao Mai, Tiancheng Cong, Xiaofeng Yin, Xuemeng Yin, Xuefei Emad, Hazim Abdallah, Ahmed Yasser, Yahya Elshahat, Dalia Elbaz, Esraa Li, Zhan Kuang, Wenqing Luo, Ziwei Gustafsson, Fredrik K. Zhao, Zheng Sjölund, Jens Schön, Thomas B. Zhang, Zhao Wei, Yanyan Wang, Junhu Zhao, Suiyi Zheng, Huan Guo, Jin Sun, Yangfan Liu, Tianli Hao, Dejun Jiang, Kui Sarvaiya, Anjali Prajapati, Kalpesh Patra, Ratnadeep Barik, Pragnesh Rathod, Chaitanya Upla, Kishor Raja, Kiran Ramachandra, Raghavendra Busch, Christoph ETcTI Universitatea Politehnica Timisoara Romania ICTEAM UCL Belgium Computer Vision Lab University of Wuerzburg Germany Computer Vision Lab ETH Zurich Switzerland Department of Electrical and Computer Engineering McMaster University Canada Department of Electrical and Computer Engineering University of Alberta Canada McMaster University Canada Xidian University China Research Institute Singapore National University of Singapore Singapore University of Sydney Australia Robotics and Internet-of-Things Laboratory Prince Sultan University Riyadh12435 Saudi Arabia Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Wuhan University of Technology China Singapore Management University Singapore Singapore Sun Yat-sen University China Electrical Engineering Department Pennsylvania State University United States The University of Sydney Australia Southeast University China University of California Los Angeles United States Beijing Jiaotong University China Mansoura Univeristy Egypt College of Information Science and Technology Jinan University China Department of Information Technology Uppsala University Sweden Hefei University of Technology China Zhejiang Dahua Technology China Sardar Vallabhbhai National Institute of Technology India Norwegian University of Science and Technology Norway
This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50... 详细信息
来源: 评论
Open-set face recognition for small galleries using siamese networks
arXiv
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arXiv 2021年
作者: Salomon, Gabriel Britto, Alceu Vareto, Rafael H. Schwartz, William R. Menotti, David Vision Robotics and Imaging Laboratory Universidade Federal Do Paraná 82590300 Brazil Ppgia Pontifícia Universidade Católica Do Paraná 80215901 Brazil Smart Sense Laboratory Department of Computer Science Universidade Federal de Minas Gerais 31270901 Brazil
Face recognition has been one of the most relevant and explored fields of Biometrics. In real-world applications, face recognition methods usually must deal with scenarios where not all probe individuals were seen dur... 详细信息
来源: 评论
VideoPipe 2022 Challenge: Real-World Video Understanding for Urban Pipe Inspection
arXiv
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arXiv 2022年
作者: Liu, Yi Zhang, Xuan Li, Ying Liang, Guixin Jiang, Yabing Qiu, Lixia Tang, Haiping Xie, Fei Yao, Wei Dai, Yi Qiao, Yu Wang, Yali ShenZhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China Shenzhen Bwell Technology Co. Ltd China Shenzhen Longhua Drainage Co. Ltd China Shanghai AI Laboratory Shanghai China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society China
Video understanding is an important problem in computer vision. Currently, the well-studied task in this research is human action recognition, where the clips are manually trimmed from the long videos, and a single cl... 详细信息
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Few-Shot Medical Image Segmentation with High-Fidelity Prototypes
arXiv
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arXiv 2024年
作者: Tang, Song Yan, Shaxu Qi, Xiaozhi Gao, Jianxin Ye, Mao Zhang, Jianwei Zhu, Xiatian IMI Group School of Health Sciences and Engineering University of Shanghai for Science and Technology Shanghai China TAMS Group Department of Informatics Universität Hamburg Hamburg Germany School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Surrey Institute for People-Centred Artificial Intelligence Centre for Vision Speech and Signal Processing University of Surrey Guildford United Kingdom Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China
Few-shot Semantic Segmentation (FSS) aims to adapt a pretrained model to new classes with as few as a single labelled training sample per class. Despite the prototype based approaches have achieved substantial success... 详细信息
来源: 评论