Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture

In this paper we address three different computer vision tasks using a single basic architecture: depth prediction, surface normal estimation, and semantic labeling. We use a multiscale convolutional network that is able to adapt easily to each task using only small modifications, regressing from the input image to the output map directly... (read more)

PDF Abstract ICCV 2015 PDF ICCV 2015 Abstract

Datasets


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Monocular Depth Estimation NYU-Depth V2 Eigen et al. RMSE 0.641 # 28

Methods used in the Paper


METHOD TYPE
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