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Promoting CNNs with Cross-Architecture Knowledge Distillation for Efficient Monocular Depth Estimation
In this paper, we propose a cross-architecture knowledge distillation method for MDE, dubbed DisDepth, to enhance efficient CNN models with the supervision of state-of-the-art transformer models.
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