Lost and Found

Introduced by Pinggera et al. in Lost and Found: Detecting Small Road Hazards for Self-Driving Vehicles

Lost and Found is a novel lost-cargo image sequence dataset comprising more than two thousand frames with pixelwise annotations of obstacle and free-space and provide a thorough comparison to several stereo-based baseline methods. The dataset will be made available to the community to foster further research on this important topic.

Source: Lost and Found: Detecting Small Road Hazards for Self-Driving Vehicles

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