Self-Supervised Underwater Image Generation for Underwater Domain Pre-Training
文献类型：期刊论文
| 作者 | Wu, Zhiheng1,2 ; Wu, Zhengxing1,2; Chen, Xingyu3; Lu, Yue1,2; Yu, Junzhi3
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| 刊名 | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
 |
| 出版日期 | 2024 |
| 卷号 | 73页码:14 |
| 关键词 | Object detection pre-training self-supervised learning semantic segmentation underwater image generation |
| ISSN号 | 0018-9456 |
| DOI | 10.1109/TIM.2024.3373105 |
| 通讯作者 | Wu, Zhengxing(zhengxing.wu@ia.ac.cn) |
| 英文摘要 | The rapid progress in computer vision has presented new opportunities for enhancing the visual capabilities of underwater robots. However, most deep learning-based visual perception algorithms often underperform due to the scarcity of underwater datasets. To address this issue, we propose an underwater image synthesis method for pre-training in the underwater domain. By leveraging self-supervised learning, we simulate the physical imaging process of underwater scenes, allowing for style transfer from in-air images to underwater images using a reduced amount of underwater data. Furthermore, we propose a pre-training strategy that utilizes synthetic underwater images to enhance underwater visual perception. Finally, abundant experiments are conducted, including quantitative and qualitative comparisons. The results validate the effectiveness and superiority of the proposed underwater image synthesis method, highlighting the substantial improvement in underwater environment perception achieved through the underwater domain pre-training (UDP) strategy. |
| 资助项目 | Beijing Natural Science Foundation |
| WOS研究方向 | Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| WOS记录号 | WOS:001184952300028 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | Beijing Natural Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/58048]  |
| 专题 | 复杂系统管理与控制国家重点实验室_水下机器人 |
| 通讯作者 | Wu, Zhengxing |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Lab Cognit & Decis Intelligence Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, State Key Lab Turbulence & Complex Syst,BIC ESAT, Beijing 100871, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wu, Zhiheng,Wu, Zhengxing,Chen, Xingyu,et al. Self-Supervised Underwater Image Generation for Underwater Domain Pre-Training[J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,2024,73:14. |
| APA | Wu, Zhiheng,Wu, Zhengxing,Chen, Xingyu,Lu, Yue,&Yu, Junzhi.(2024).Self-Supervised Underwater Image Generation for Underwater Domain Pre-Training.IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,73,14. |
| MLA | Wu, Zhiheng,et al."Self-Supervised Underwater Image Generation for Underwater Domain Pre-Training".IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 73(2024):14. |
入库方式： OAI收割
来源：自动化研究所
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