Three-Filters-to-Normal VS rethinking_road_reconstruction_pothole_detection

Compare Three-Filters-to-Normal vs rethinking_road_reconstruction_pothole_detection and see what are their differences.

Three-Filters-to-Normal

Three-Filters-to-Normal: An Accurate and Ultrafast Surface Normal Estimator (RAL+ICRA'21) (by ruirangerfan)

rethinking_road_reconstruction_pothole_detection

Rethinking Road Surface 3D Reconstruction and Pothole Detection: From Perspective Transformation to Disparity Map Segmentation (T-CYB) (by ruirangerfan)
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Three-Filters-to-Normal rethinking_road_reconstruction_pothole_detection
1 1
95 7
- -
1.8 6.0
over 2 years ago over 3 years ago
C++
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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Three-Filters-to-Normal

Posts with mentions or reviews of Three-Filters-to-Normal. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-29.

rethinking_road_reconstruction_pothole_detection

Posts with mentions or reviews of rethinking_road_reconstruction_pothole_detection. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-29.

What are some alternatives?

When comparing Three-Filters-to-Normal and rethinking_road_reconstruction_pothole_detection you can also consider the following projects:

unsupervised_disparity_map_segmentation - Road Damage Detection Based on Unsupervised Disparity Map Segmentation (T-ITS)

SNE-RoadSeg - SNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020

napkinXC - Extremely simple and fast extreme multi-class and multi-label classifiers.

road_surface_3d_reconstruction_datasets - Road Surface 3D Reconstruction Based on Dense Subpixel Disparity Map Estimation (T-IP)