失物招领数据集

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）。

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

数据使用许可协议：

许可证.txt

	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