FlexDepth proposes a scale-driven family of self-supervised MDE models with two-stage training and SDD decoder claiming SOTA performance and low compute on driving benchmarks.
IEEE Sensors Journal21(24), 27225–27237 (2021) 25
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Towards Robust Driving Perception: A Flexible Scale-Driven Family for Self-Supervised Monocular Depth Estimation
FlexDepth proposes a scale-driven family of self-supervised MDE models with two-stage training and SDD decoder claiming SOTA performance and low compute on driving benchmarks.