mlsanityData to 14 Oct 2026

Lightweight Monocular Depth Estimation

arXiv 2212.11363 ↗First posted 21 Dec 2022cs.CVcited by 0

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Abstract (arXiv)

Monocular depth estimation can play an important role in addressing the issue of deriving scene geometry from 2D images. It has been used in a variety of industries, including robots, self-driving cars, scene comprehension, 3D reconstructions, and others. The goal of our method is to create a lightweight machine-learning model in order to predict the depth value of each pixel given only a single RGB image as input with the Unet structure of the image segmentation network. We use the NYU Depth V2 dataset to test the structure and compare the result with other methods. The proposed method achieves relatively high accuracy and low rootmean-square error.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 21 of its 45 references that are in the map. First posted on arXiv 21 Dec 2022.

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21 of 45 references.

References · 21

  1. 2017Attention Is All You Needcited by 60,361
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  10. 2014Depth Map Prediction from a Single Image using a Multi-Scale Deep Networkcited by 1,274
  11. 2016Unsupervised Monocular Depth Estimation with Left-Right Consistencycited by 820
  12. 2018Deep Ordinal Regression Network for Monocular Depth Estimationcited by 723
9 more
  1. 2014Recurrent Models of Visual Attentioncited by 349
  2. 2018DeepMVS: Learning Multi-view Stereopsiscited by 277
  3. 2016DeMoN: Depth and Motion Network for Learning Monocular Stereocited by 201
  4. 2018High Quality Monocular Depth Estimation via Transfer Learningcited by 133
  5. 2017Semi-Supervised Deep Learning for Monocular Depth Map Predictioncited by 109
  6. 2021TransformerFusion: Monocular RGB Scene Reconstruction using Transformerscited by 106
  7. 2017Monocular Depth Estimation with Hierarchical Fusion of Dilated CNNs and Soft-Weighted-Sum Inferencecited by 24
  8. 2021Universal Background Subtraction based on Arithmetic Distribution Neural Networkcited by 11
  9. 2020Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applicationscited by 6

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