├── README.md
└── 水下目标检测竞赛介绍（光学）20200305.pdf


/README.md:
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  1 | # Underwater Object Detection [Optical]
  2 | 
  3 | 
  4 | ### Papers
  5 |   
  6 |   * **Reveal of Domain Effect:** Xingyu Chen, Yue Lu, Zhengxing Wu, Junzhi Yu, Li Wen. <br />
  7 |   `"Reveal of Domain Effect: How Visual Restoration Contributes to Object Detection in Aquatic Scenes."`  ArXiv (2020).
  8 |   [[paper](https://arxiv.org/abs/2003.01913)] **Very Interesting Insights on Image Restoration and Object Detection!!**:star2: 
  9 |     
 10 |   * **SWIPENet+IMA:** Long Chen, Zhihua Liu, Lei Tong, Zheheng Jiang, Shengke Wang, Junyu Dong, Huiyu Zhou. <br />
 11 |   `"Underwater Object Detection using Invert Multi-Class Adaboost with Deep Learning."` ArXiv (2020).
 12 |    [[paper](https://arxiv.org/abs/2005.11552)] 
 13 |   
 14 | * **RoIMix:** Wei-Hong Lin, Jia-Xing Zhong, Shan Liu, Thomas Li, Ge Li. <br />
 15 |   `"RoIMix: Proposal-Fusion among Multiple Images for Underwater Object Detection."` ArXiv (2019).
 16 |   [[paper](https://arxiv.org/abs/1911.03029)] 
 17 |   [[知乎](https://zhuanlan.zhihu.com/p/100398417)] 
 18 |   
 19 | * Xingyu Chen, Zhengxing Wu, Junzhi Yu, Li Wen. <br />
 20 |   `"Rethinking Temporal Object Detection from Robotic Perspectives."` ArXiv (2019).
 21 |   [[paper](https://arxiv.org/abs/1912.10406)] 
 22 |   
 23 | * Hong Liu, Pinhao Song, Runwei Ding. <br />
 24 |   `"WQT and DG-YOLO: Towards Domain Generalization in Underwater Object Detection."` ArXiv (2020).
 25 |   [[paper](https://arxiv.org/abs/2004.06333)]   
 26 |   
 27 | *  Hongbo Yang, Ping Liu, YuZhen Hu, JingNan Fu. <br />
 28 |   `"Research on Underwater Object Recognition Based on YOLOv3."` Microsystem Technologies (2020). 
 29 |   [[paper](https://link.springer.com/article/10.1007/s00542-019-04694-8)] 
 30 |   
 31 | * Hui Li, Xi Yang, ZhenMing Li, TianLun Zhang. <br />
 32 |   `"Underwater image enhancement with Image Colorfulness Measure."` ArXiv (2020). 
 33 |   [[paper](https://arxiv.org/abs/2004.08609)]   
 34 |   
 35 | * Sen Lin, Kaichen Chi. <br />
 36 |   `"Underwater Image Enhancement Based on Structure-Texture Reconstruction."` ArXiv (2020). 
 37 |   [[paper](https://arxiv.org/abs/2004.05430)]   
 38 | 
 39 | * Monika Roznere, Alberto Quattrini Li. <br />
 40 |   `"Real-time Model-based Image Color Correction for Underwater Robots."` ArXiv (2020). 
 41 |   [[paper](https://arxiv.org/abs/1904.06437)]     
 42 |   
 43 | * **UWCNN:** Chongyi Li, Saeed Anwar, Fatih Porikli. <br />
 44 |   `"Underwater Scene Prior Inspired Deep Underwater Image and Video Enhancement."` Pattern Recognition (2020).
 45 |   [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320319303401)] 
 46 |   [[code](https://github.com/saeed-anwar/UWCNN)]   
 47 |   
 48 | * Yuan Zhou, Kangming Yan. <br />
 49 |   `"Domain Adaptive Adversarial Learning Based on Physics Model Feedback for Underwater Image Enhancement."` ArXiv (2020). 
 50 |   [[paper](https://arxiv.org/abs/2002.09315)]   
 51 |   
 52 | * **UWGAN:** Nan Wang, Yabin Zhou, Fenglei Han, Haitao Zhu, Yaojing Zheng. <br />
 53 |   `"UWGAN: Underwater GAN for Real-world Underwater Color Restoration and Dehazing."` ArXiv (2019).
 54 |   [[paper](https://arxiv.org/abs/1912.10269)] 
 55 |   [[code](https://github.com/infrontofme/UWGAN_UIE)]  
 56 |   
 57 |  * **AIO:** Pritish Uplavikar, Zhenyu Wu, Zhangyang Wang. <br /> 
 58 |    `"All-In-One Underwater Image Enhancement using Domain-Adversarial Learning."` CVPRW (2019).
 59 |    [[paper](http://openaccess.thecvf.com/content_CVPRW_2019/html/UG2_Prize_Challenge/Uplavikar_All-in-One_Underwater_Image_Enhancement_Using_Domain-Adversarial_Learning_CVPRW_2019_paper.html)]
 60 |    [[code](https://github.com/TAMU-VITA/All-In-One-Underwater-Image-Enhancement-using-Domain-Adversarial-Learning)]  
 61 |   
 62 |  * **UWStereoNet:** Katherine A. Skinner, Junming Zhang, Elizabeth A. Olson, Matthew Johnson-Roberson. <br />
 63 |   `"UWStereoNet: Unsupervised Learning for Depth Estimation and Color Correction of Underwater Stereo Imagery."` ICRA (2019).
 64 |   [[paper](https://ieeexplore.ieee.org/document/8794272)] 
 65 |   [[code](https://github.com/junming259/UWStereoNet_disparity)]`Only for Disparity`   
 66 | 
 67 | * **Water-Net:** Chongyi Li, Chunle Guo, Wenqi Ren, Runmin Cong, Junhui Hou, Sam Kwong, Dacheng Tao. <br />
 68 |   `"An Underwater Image Enhancement Benchmark Dataset and Beyond."` IEEE Transactions on Image Processing (2019)
 69 |   [[paper](https://arxiv.org/pdf/1901.05495.pdf)] 
 70 |   [[project](https://github.com/Li-Chongyi/Water-Net_Code)]
 71 |   
 72 | * **WaterGAN:** Jie Li, Katherine A. Skinner, Ryan Eustice, M. Johnson-Roberson. <br />
 73 |   `"WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images."` IEEE Robotics and Automation Letters (2017).
 74 |   [[paper](https://arxiv.org/abs/1702.07392)] 
 75 |   [[code](https://github.com/kskin/WaterGAN)]
 76 |   
 77 |   
 78 | ### Benchmarks & Surverys
 79 | 
 80 | * **RUIE:** Risheng Liu, Xin Fan, Ming Zhu, Minjun Hou, Zhongxuan Luog. <br />
 81 |   `"Real-world Underwater Enhancement: Challenges, Benchmarks, and Solution."` ArXiv (2019).
 82 |   [[paper](https://arxiv.org/abs/1901.05320)] 
 83 |   [[project](https://github.com/dlut-dimt/Underwater-image-enhancement-algorithms)]  
 84 |  
 85 | * **UDD:** Zhihui Wang, Chongwei Liu, Shijie Wang, Tao Tang, Yulong Tao, Caifei Yang, Haojie Li, Xing Liu, Xin Fan. <br />
 86 |   `"An Underwater Open-sea Farm Object Detection Dataset for Underwater Robot Picking."`
 87 |    [[paper](https://arxiv.org/pdf/2003.01446)] 
 88 | 
 89 | * **UIEB:** Chongyi Li, Chunle Guo, Wenqi Ren, Runmin Cong, Junhui Hou, Sam Kwong, Dacheng Tao. <br />
 90 |   `"An Underwater Image Enhancement Benchmark Dataset and Beyond."` IEEE TIP (2019)
 91 |   [[paper](https://arxiv.org/pdf/1901.05495.pdf)] 
 92 |   [[project](https://li-chongyi.github.io/proj_benchmark.html)]
 93 |   
 94 | * **OUC:** Long Chen, Lei Tong, Feixiang Zhou, Zheheng Jiang, Zhenyang Li, Jialin Lv, Junyu Dong, Huiyu Zhou. <br /> 
 95 |   `"A Benchmark Dataset for both Underwater Image Enhancement and Underwater Object Detection."` ArXiv (2020).  
 96 |   [[paper](https://arxiv.org/abs/2006.15789)] 
 97 |   
 98 | * Yan Wang, Wei Song, Giancarlo Fortino, Li-Zhe Qi, Wenqiang Zhang, Antonio Liotta. <br />
 99 |   `"An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging."` IEEE Access (2019).
100 |   [[paper](https://ieeexplore.ieee.org/document/8782094)] 
101 |   [[code](https://github.com/wangyanckxx/Single-Underwater-Image-Enhancement-and-Color-Restoration)] 
102 |   
103 | * Saeed Anwar, Chongyi Li, Fatih Porikli. <br />
104 |   `"Deep Underwater Image Enhancement."` ArXiv (2018).
105 |   [[paper](https://arxiv.org/abs/1807.03528)] 
106 |   
107 | * Min Han, Zhiyu Lyu, Tie Qiu, Meiling Xu. <br />
108 |   `"A Review on Intelligence Dehazing and Color Restoration for Underwater Images."` 
109 |   IEEE Transactions on Systems, Man, and Cybernetics: Systems (2018).
110 |   [[paper](https://ieeexplore.ieee.org/document/8267119)]   
111 |   
112 |   
113 | ### 中文文献
114 | 
115 | * 朱世伟，杭仁龙，刘青山. <br /> 
116 |   `"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)
117 |   [[论文](https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ&dbname=CJFDLAST2020&filename=NJSF202001020&v=MDkwMjNMdXhZUzdEaDFUM3FUcldNMUZyQ1VSN3FmWU9abkZ5N2hWYnJMS3lmWWFMRzRITkhNcm85SFpJUjhlWDE=)] 
118 | 
119 | * 徐凤强，董鹏，王辉兵，付先平. <br /> 
120 |   `"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)
121 |   [[论文](https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ&dbname=CJFDLAST2020&filename=BJHK201912006&v=MjExODk5ak5yWTlGWW9SOGVYMUx1eFlTN0RoMVQzcVRyV00xRnJDVVI3cWZZT1puRnk3aFdyL0xKeWZEWmJHNEg=)] 
122 |   
123 | * 刘有用，张江梅，王坤朋，冯兴华，杨秀洪.  
124 |   `"不平衡数据集下的水下目标快速识别方法."` 计算机工程与应用 (2019)
125 |    [[论文](http://kns.cnki.net/KCMS/detail/11.2127.TP.20190719.1443.018.html)]
126 |   
127 | 
128 | ### Related Resources
129 | 
130 | * **水下目标检测竞赛介绍(光学)202003**
131 |   [[Slides](https://github.com/wangdongdut/Underwater-Object-Detection/blob/master/%E6%B0%B4%E4%B8%8B%E7%9B%AE%E6%A0%87%E6%A3%80%E6%B5%8B%E7%AB%9E%E8%B5%9B%E4%BB%8B%E7%BB%8D%EF%BC%88%E5%85%89%E5%AD%A6%EF%BC%8920200305.pdf)] 
132 |   [[Video1](https://www.bilibili.com/video/BV1yE411u7fm?from=search&seid=6344384280060127467)]
133 |   [[Video2](https://www.bilibili.com/video/BV1kE411P7hm?from=search&seid=6344384280060127467)]
134 | 
135 | * **some underwater datasets:** https://github.com/xahidbuffon/underwater_datasets
136 | 
137 | * **detectron2:** https://github.com/facebookresearch/detectron2  <br />
138 |   [[model zoo](https://github.com/facebookresearch/detectron2/blob/master/MODEL_ZOO.md)]
139 |   [[detectron](https://github.com/facebookresearch/Detectron/)]
140 |   [[maskrcnn-benchmark](https://github.com/facebookresearch/maskrcnn-benchmark)]
141 | 
142 | * **mmdetection:** https://github.com/open-mmlab/mmdetection <br />
143 |   [[model zoo](https://github.com/open-mmlab/mmdetection/blob/master/docs/MODEL_ZOO.md)]
144 |   
145 | * **tensorflow detection model zoo:** https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
146 |   
147 | * **simpledet:** https://github.com/TuSimple/simpledet <br />
148 |   [[model zoo](https://github.com/TuSimple/simpledet/blob/master/MODEL_ZOO.md)]
149 |   
150 | * **darknet/yolo:** https://pjreddie.com/darknet/
151 | 
152 | * **awesome-object-detection:** https://github.com/amusi/awesome-object-detection
153 | 
154 | * Zhengxia Zou, Zhenwei Shi, Yuhong Guo, Jieping Ye. <br /> 
155 |   `"Object Detection in 20 Years: A Survey."` ArXiv (2019).
156 |   [[paper](https://arxiv.org/abs/1905.05055)]:star2:  
157 | 
158 | * Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth, Jie Chen, Xinwang Liu, Matti Pietikäinen. <br /> 
159 |   `"Deep Learning for Generic Object Detection: A Survey."` 
160 |   IJCV (2019).
161 |   [[paper](https://link.springer.com/article/10.1007/s11263-019-01247-4)]:star2:
162 |   
163 | * Zhi Zhang, Tong He, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li. <br /> 
164 |   `"Bag of Freebies for Training Object Detection Neural Networks."` 
165 |   ArXiv (2019). [[paper](https://arxiv.org/abs/1902.04103)]:star2:
166 |   
167 | * **About Anchor-free Object Detection:** <br /> 
168 |   [[AnchorFreeDetectionList](https://github.com/VCBE123/AnchorFreeDetection)] <br /> 
169 |   [[物体检测的轮回: anchor-based 与 anchor-free](https://zhuanlan.zhihu.com/p/62372897)]
170 |   
171 | * **TensorRT:** https://developer.nvidia.com/tensorrt
172 | 
173 | * **TVM:** https://tvm.apache.org/
174 | 
175 | ### Related Codes:star2::star2::star2:   
176 |   
177 | * https://github.com/milleniums/underwater-object-detection-mmdetection
178 | 
179 | * https://github.com/DataXujing/EfficientDet_pytorch
180 | 
181 | * https://github.com/sankin97/Underwater_detection
182 | 
183 | * https://github.com/zhengye1995/underwater-object-detection
184 | 
185 | * https://github.com/Wakinguup/Underwater_detection
186 | 
187 | ### Detection Reports:  
188 | * [**目标检测的过去、现在与将来**[俞刚-深蓝学院公开课]](https://www.bilibili.com/video/BV1154y1v7BZ?from=search&seid=11991442565688432154)：https://www.bilibili.com/video/BV1154y1v7BZ?from=search&seid=11991442565688432154
189 | 
190 | * [**视觉目标检测年度进展概述**[VALSE 2020 APR-叶齐祥]](https://www.bilibili.com/video/BV19V411z7L3?from=search&seid=12691654838979826409)：https://www.bilibili.com/video/BV19V411z7L3?from=search&seid=12691654838979826409
191 | 
192 | * [**深度目标检测**[Valse Webinar 20200429]](https://www.bilibili.com/video/BV1kt4y1y7E3?from=search&seid=12410496426535668823)：https://www.bilibili.com/video/BV1kt4y1y7E3?from=search&seid=12410496426535668823
193 | 
194 | * [**基于深度学习的目标检测技术**[深度学习大讲堂]](https://www.bilibili.com/video/BV1JW411n7cP)：https://www.bilibili.com/video/BV1JW411n7cP 
195 | 
196 | * [**Detection and Segmentation**[Stanford University CS231n]](https://www.youtube.com/watch?v=nDPWywWRIRo&list=PLC1qU-LWwrF64f4QKQT-Vg5Wr4qEE1Zxk&index=11): https://www.youtube.com/watch?v=nDPWywWRIRo&list=PLC1qU-LWwrF64f4QKQT-Vg5Wr4qEE1Zxk&index=11
197 | 
198 | 
199 | ### 比赛相关:  
200 | 
201 | * **Old Data**
202 |   [[下载地址](https://pan.baidu.com/s/1puJ0BRvoTTaPjk4_KzhEKw)(0hct)]
203 | 
204 | * **比赛经验**
205 |   * `天池CV赛事老司机，手把手带你入门目标检测赛题`[[Video](https://www.bilibili.com/video/BV1T54y197Xt?from=search&seid=13601651463352031714)][[blog](https://blog.csdn.net/qq_40662074/article/details/104975300)]
206 |   * `Kaggle实战目标检测奇淫技巧合集`[[blog](https://mp.weixin.qq.com/s?__biz=MzIwMTE1NjQxMQ==&mid=2247487104&idx=1&sn=a41a6e37be1e169b316d67765d2d9eae&chksm=96f37cd4a184f5c2abb99b5e050642df5e82f172beb19a06c562b91b610f9ed624eb46a2ec81&mpshare=1&scene=23&srcid=#rd)]
207 | 


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