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LostandFound数据集 包含112 个立体声视频序列

LostandFound数据集 包含112 个立体声视频序列

Scene:

Action/Event Detection

Data Type:

Classification
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致力于人工智能业务的研究、数据集处理。

Data Preview ? 45.7G

    LostandFound 数据集解决了检测路上通常由货物丢失造成的意外小障碍物的问题。

    该数据集包括 112 个立体声视频序列,具有 2104 个带注释帧(从记录的数据中大约每十分之一帧选取一帧)。

    数据结构:


    gtCoarse.zip (37MB) annotations for train and test sets
    (2104 annotated images)
    leftImg8bit.zip(6GB) left 8-bit images - train and test set
    rightImg8bit.zip (6GB) right 8-bit images - train and test set
    leftImg16bit.zipl (17GB) right 16-bit images - train and test set
    (2104 images)
    rightImg16bit.zip (17GB) right 16-bit images - train and test set
    (2104 images)
    disparity.zip (1.4GB) depth maps using Semi-Global Matching for                
    train and test set (2104 images)
    timestamp.tgz (50kB) timestamps for train and test sets
    camera.zip (1MB) Intrinsic and extrinsic camera parameters for
    train and test sets
    vehicle.zip (1MB) vehicle odometry data (speed and yaw rate)
    for train and test sets


    论文引用:

    Peter Pinggera, Sebastian Ramos, Stefan Gehrig, Uwe Franke, Carsten Rother, Rudolf Mester, "Lost and Found: Detecting Small Road Hazards for Self-Driving Vehicles", Proceedings of IROS 2016, Daejeon, Korea. link to the paper


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