road_surface_3d_reconstruction_datasets VS unsupervised_disparity_map_segmentation

Compare road_surface_3d_reconstruction_datasets vs unsupervised_disparity_map_segmentation and see what are their differences.

road_surface_3d_reconstruction_datasets

Road Surface 3D Reconstruction Based on Dense Subpixel Disparity Map Estimation (T-IP) (by ruirangerfan)
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road_surface_3d_reconstruction_datasets unsupervised_disparity_map_segmentation
1 2
19 13
- -
4.1 3.9
over 3 years ago over 3 years ago
MATLAB 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.

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.

unsupervised_disparity_map_segmentation

Posts with mentions or reviews of unsupervised_disparity_map_segmentation. 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 road_surface_3d_reconstruction_datasets and unsupervised_disparity_map_segmentation you can also consider the following projects:

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

openMVS - open Multi-View Stereo reconstruction library

rethinking_road_reconstruction_pothole_detection - Rethinking Road Surface 3D Reconstruction and Pothole Detection: From Perspective Transformation to Disparity Map Segmentation (T-CYB)

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