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RoIMix: Wei-Hong Lin, Jia-Xing Zhong, Shan Liu, Thomas Li, Ge Li.
"RoIMix: Proposal-Fusion among Multiple Images for Underwater Object Detection."
ArXiv (2019). [paper] [知乎] -
Hongbo Yang, Ping Liu, YuZhen Hu, JingNan Fu.
"Research on Underwater Object Recognition Based on YOLOv3."
Microsystem Technologies (2020). [paper] -
UWCNN: Chongyi Li, Saeed Anwar, Fatih Porikli.
"Underwater Scene Prior Inspired Deep Underwater Image and Video Enhancement."
Pattern Recognition (2020). [paper] [code] -
UWGAN: Nan Wang, Yabin Zhou, Fenglei Han, Haitao Zhu, Yaojing Zheng.
"UWGAN: Underwater GAN for Real-world Underwater Color Restoration and Dehazing."
ArXiv (2019). [paper] [code] -
UWStereoNet: Katherine A. Skinner, Junming Zhang, Elizabeth A. Olson, Matthew Johnson-Roberson.
"UWStereoNet: Unsupervised Learning for Depth Estimation and Color Correction of Underwater Stereo Imagery."
ICRA (2019). [paper] [code]Only for Disparity
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Water-Net: Chongyi Li, Chunle Guo, Wenqi Ren, Runmin Cong, Junhui Hou, Sam Kwong, Dacheng Tao.
"An Underwater Image Enhancement Benchmark Dataset and Beyond."
IEEE Transactions on Image Processing (2019) [paper] [project] -
WaterGAN: Jie Li, Katherine A. Skinner, Ryan Eustice, M. Johnson-Roberson.
"WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images."
IEEE Robotics and Automation Letters (2017). [paper] [code]
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RUIE: Risheng Liu, Xin Fan, Ming Zhu, Minjun Hou, Zhongxuan Luog.
"Real-world Underwater Enhancement: Challenges, Benchmarks, and Solution."
ArXiv (2019). [paper] [project] -
UIEB: Chongyi Li, Chunle Guo, Wenqi Ren, Runmin Cong, Junhui Hou, Sam Kwong, Dacheng Tao.
"An Underwater Image Enhancement Benchmark Dataset and Beyond."
IEEE TIP (2019) [paper] [project] -
Saeed Anwar, Chongyi Li, Fatih Porikli.
"Deep Underwater Image Enhancement."
ArXiv (2018). [paper] -
Min Han, Zhiyu Lyu, Tie Qiu, Meiling Xu.
"A Review on Intelligence Dehazing and Color Restoration for Underwater Images."
IEEE Transactions on Systems, Man, and Cybernetics: Systems (2018). [paper] -
URPC2018: [download from Google Drive] [download from DUT Pan]
This dataset is for the URPC2018 challenge (http://2018.cnurpc.org/) and is for research purpose only.
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朱世伟,杭仁龙,刘青山.
"基于类加权YOLO网络的水下目标检测."
南京师大学报(自然科学版) (2020) [论文] -
徐凤强,董鹏,王辉兵,付先平.
"基于水下机器人的海产品智能检测与自主抓取系统."
北京航空航天大学学报 (2019) [论文]
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水下目标检测竞赛介绍(光学)202003 [Slides]
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some underwater datasets: https://github.com/xahidbuffon/underwater_datasets
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tensorflow detection model zoo: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
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detectron2: https://github.com/facebookresearch/detectron2
[detectron] -
mmdetection: https://github.com/open-mmlab/mmdetection
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darknet/yolo: https://pjreddie.com/darknet/
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awesome-object-detection: https://github.com/amusi/awesome-object-detection
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Object Detection in 20 Years: A Survey: Zhengxia Zou, Zhenwei Shi, Yuhong Guo, Jieping Ye.
"Object Detection in 20 Years: A Survey."
ArXiv (2019). [paper]