Self-Supervised Relative Depth Learning for Urban Scene Understanding

ECCV 2018 Huaizu JiangErik Learned-MillerGustav LarssonMichael MaireGreg Shakhnarovich

As an agent moves through the world, the apparent motion of scene elements is (usually) inversely proportional to their depth. It is natural for a learning agent to associate image patterns with the magnitude of their displacement over time: as the agent moves, faraway mountains don't move much; nearby trees move a lot... (read more)

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