DSM Refinement with Deep Encoder-Decoder Networks

by   Nando Metzger, et al.

3D city models can be generated from aerial images. However, the calculated DSMs suffer from noise, artefacts, and data holes that have to be manually cleaned up in a time-consuming process. This work presents an approach that automatically refines such DSMs. The key idea is to teach a neural network the characteristics of urban area from reference data. In order to achieve this goal, a loss function consisting of an L1 norm and a feature loss is proposed. These features are constructed using a pre-trained image classification network. To learn to update the height maps, the network architecture is set up based on the concept of deep residual learning and an encoder-decoder structure. The results show that this combination is highly effective in preserving the relevant geometric structures while removing the undesired artefacts and noise.



There are no comments yet.


page 1

page 2

page 5


End-to-end Trained CNN Encode-Decoder Networks for Image Steganography

All the existing image steganography methods use manually crafted featur...

Encoder-decoder semantic segmentation models for electroluminescence images of thin-film photovoltaic modules

We consider a series of image segmentation methods based on the deep neu...

A Generalized Multi-Task Learning Approach to Stereo DSM Filtering in Urban Areas

City models and height maps of urban areas serve as a valuable data sour...

Pointfilter: Point Cloud Filtering via Encoder-Decoder Modeling

Point cloud filtering is a fundamental problem in geometry modeling and ...

Not quite there yet: Combining analogical patterns and encoder-decoder networks for cognitively plausible inflection

The paper presents four models submitted to Part 2 of the SIGMORPHON 202...

Attention-based Residual Speech Portrait Model for Speech to Face Generation

Given a speaker's speech, it is interesting to see if it is possible to ...

Light-weight Document Image Cleanup using Perceptual Loss

Smartphones have enabled effortless capturing and sharing of documents i...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.