Introduction

Marine wastes are severely threatening marine animals and their habitat, also causing an impact on human life through toxic substances transportation and accumulation. To prevent the wastes especially the plastic trash from getting into the ocean, it is essential to detect and clean the floating wastes in inland waters efficiently.

FloW is the first dataset for floating waste detection in inland waters. It contains a vision-based sub-dataset, FloW-Img, and a multimodal dataset, FloW-RI which contains the spatial and temporal calibrated image and millimeter-wave radar data. Detailed information can be found in the pages for the two sub-dataset.

By publishing Flow, it is hoped that more attention from research communities could be paid to floating waste detection in inland waters as well as the challenging small object detection over the water surface. In addition, waste detection based on millimeter-wave radar data or the fusion of image and radar data is also a novel task and FloW provides accessible real-world data.

Click the items in the sidebar panel to choose the data that you want to download, and apply for downloading on corresponding pages.

If you have any questions related to our dataset, please email datasets@orca-tech.com.cn.

About Radar

If you are interested in the millimeter wave radar used in the dataset or need to order the radar for research, click to [get more information about the millimeter wave radar] .

关于雷达

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Citation

Our paper has been accepted by ICCV2021. To know more details about FloW dataset, our paper can be found here. If you find our dataset useful for your research, you can cite:

  @InProceedings{Cheng_2021_ICCV,
    author = {Cheng, Yuwei and Zhu, Jiannan and Jiang, Mengxin and Fu, Jie and Pang, Changsong and Wang, Peidong and Sankaran, Kris and Onabola, Olawale and Liu, Yimin and Liu, Dianbo and Bengio, Yoshua},
    title = {FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month = {October},
    year = {2021},
    pages = {10953-10962}
  }