「CV」 水下摄影资源汇总

通用目标检测资源、GAN 资源、自编码器资源

1 综述

1. Underwater Optical Image Processing: A Comprehensive Review
   2017-02-13 paper

2. A Review on Intelligence Dehazing and Color Restoration for Underwater Images
   2018-01-23 paper

3. Deep Underwater Image Enhancement
   2018-07-10 paper

4. An Underwater Image Enhancement Benchmark Dataset and Beyond
   2019-01-11 paper | project
   UIEB 数据集
   Water-Net

5. Real-world Underwater Enhancement: Challenges, Benchmarks, and Solution
   2019-01-15 paper | project
   RUIE

6. An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging
   2019-07-07 paper | code

7. An Underwater Open-sea Farm Object Detection Dataset for Underwater Robot Picking
   2020-03-03 paper
   UDD

2 理论

3 图像增强

1. Underwater Scene Prior Inspired Deep Underwater Image and Video Enhancement
   2019-09-05 paper | tensorflow | project
   UWCNN

2. Domain Adaptive Adversarial Learning Based on Physics Model Feedback for Underwater Image Enhancement
   2020-02-20 paper

3. UWGAN: Underwater GAN for Real-world Underwater Color Restoration and Dehazing
   2019-12-21 paper | tensorflow
   UWGAN

4. All-In-One Underwater Image Enhancement using Domain-Adversarial Learning
   CVPRW 2019 2019 paper | pytorch
   AIO

5. UWStereoNet: Unsupervised Learning for Depth Estimation and Color Correction of Underwater Stereo Imagery
   ICRA 2019 2019 paper | tensorflowOnly for Disparity
   UWStereoNet

6. WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images
   2017-02-23 paper | tensorflow-official
   WaterGAN

4 目标检测

1. Reveal of Domain Effect: How Visual Restoration Contributes to Object Detection in Aquatic Scenes
   2020 paper
   Very Interesting Insights on Image Restoration and Object Detection
   Reveal of Domain Effect

2. RoIMix: Proposal-Fusion among Multiple Images for Underwater Object Detection
   2019 paper | 知乎
   RoIMix

3. Rethinking Temporal Object Detection from Robotic Perspectives
   2019 paper

4. 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 2019 徐凤强，董鹏，王辉兵，付先平 论文

5. 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 2019 刘有用，张江梅，王坤朋，冯兴华，杨秀洪 论文

6. Research on Underwater Object Recognition Based on YOLOv3
   2020 paper

7. 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 2020 朱世伟，杭仁龙，刘青山 论文

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附录

A 参考资料

1. Underwater-Object-Detection

B 数据集

URPC2018
URPC2018 challenge http://2018.cnurpc.org/
数据集： Google Drive、DUT Pan

C 推荐资料

1. 解读
   • 水下图像增强-ICRA-2019

2. 竞赛
   水下目标检测竞赛介绍(光学)202003

3. 数据集
   • some underwater datasets
4. model
   • tensorflow detection model zoo
5. 目标检测方法
   • simpledet
     model zoo

• darknet/yolo
• awesome-object-detection
• Object Detection in 20 Years: A Survey
• Deep Learning for Generic Object Detection: A Survey
• AnchorFreeDetectionList、物体检测的轮回: anchor-based 与 anchor-free

1. 训练框架
   • detectron2
     model zoo、detectron、maskrcnn-benchmark
   • mmdetection
     model zoo
2. 部署框架
   • TensorRT: https://developer.nvidia.com/tensorrt
   • TVM: https://tvm.apache.org/