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%2C which only requires single input image during the inference phase but can still produce highly accurate depth estimations comparable to rich resource based methods. Specifically%2C we treat rich-resource data as prior information and extract features from it as reference features in an offline manner. When estimating the depth for a single-image image%2C we search for similar pixels from the rich-resource features and use them as prior information to estimate the depth. Experimental results demonstrate that our model outperform other single-image model and can achieve comparable or even better performance than models with rich-resource inputs%2C only using low-resolution single-image input.?quality=80&w=800)
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