Three-Filters-to-Normal
Three-Filters-to-Normal: An Accurate and Ultrafast Surface Normal Estimator (RAL+ICRA'21) (by ruirangerfan)
road_surface_3d_reconstruction_datasets
Road Surface 3D Reconstruction Based on Dense Subpixel Disparity Map Estimation (T-IP) (by ruirangerfan)
| Three-Filters-to-Normal | road_surface_3d_reconstruction_datasets | |
|---|---|---|
| 1 | 1 | |
| 95 | 19 | |
| - | - | |
| 1.8 | 4.1 | |
| over 2 years ago | over 3 years ago | |
| C++ | MATLAB | |
| 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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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.
-
[R] Computer Vision for Driving Scene Understanding: from Autonomous Driving to Road Condition Assessment - Link to a free online lecture by the author in comments
git: https://github.com/ruirangerfan/Three-Filters-to-Normal
road_surface_3d_reconstruction_datasets
Posts with mentions or reviews of road_surface_3d_reconstruction_datasets.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-08-29.
-
[R] Computer Vision for Driving Scene Understanding: from Autonomous Driving to Road Condition Assessment - Link to a free online lecture by the author in comments
gits: https://github.com/ruirangerfan/road_surface_3d_reconstruction_datasets https://github.com/ruirangerfan/unsupervised_disparity_map_segmentation https://github.com/ruirangerfan/rethinking_road_reconstruction_pothole_detection
What are some alternatives?
When comparing Three-Filters-to-Normal and road_surface_3d_reconstruction_datasets you can also consider the following projects:
unsupervised_disparity_map_segmentation - Road Damage Detection Based on Unsupervised Disparity Map Segmentation (T-ITS)
rethinking_road_reconstruction_pothole_detection - Rethinking Road Surface 3D Reconstruction and Pothole Detection: From Perspective Transformation to Disparity Map Segmentation (T-CYB)
SNE-RoadSeg - SNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020
napkinXC - Extremely simple and fast extreme multi-class and multi-label classifiers.
Three-Filters-to-Normal vs unsupervised_disparity_map_segmentation
road_surface_3d_reconstruction_datasets vs unsupervised_disparity_map_segmentation
Three-Filters-to-Normal vs rethinking_road_reconstruction_pothole_detection
road_surface_3d_reconstruction_datasets vs SNE-RoadSeg
Three-Filters-to-Normal vs napkinXC
road_surface_3d_reconstruction_datasets vs rethinking_road_reconstruction_pothole_detection