Commit d50570f8 authored by Radim Tylecek's avatar Radim Tylecek

Update README.md

parent 7ee1ebf5
...@@ -6,6 +6,8 @@ A multi-camera rig is mounted on top of the robot, enabling the use of both ster ...@@ -6,6 +6,8 @@ A multi-camera rig is mounted on top of the robot, enabling the use of both ster
Precise ground truth for the 3D structure of the garden has been obtained with a laser scanner and accurate pose estimates for the robot are available as well. Precise ground truth for the 3D structure of the garden has been obtained with a laser scanner and accurate pose estimates for the robot are available as well.
Ground truth semantic labels and ground truth depth from a laser scan will be used for benchmarking the quality of the 3D reconstructions. Ground truth semantic labels and ground truth depth from a laser scan will be used for benchmarking the quality of the 3D reconstructions.
## Reconstruction Challenge ## Reconstruction Challenge
Given a set of images and their known camera poses, the goal of the challenge is to create a semantically annotated 3D model of the scene. Given a set of images and their known camera poses, the goal of the challenge is to create a semantically annotated 3D model of the scene.
To this end, it will be necessary to compute depth maps for the images and then fuse them together (potentially while incorporating information from the semantics) into a single 3D model. To this end, it will be necessary to compute depth maps for the images and then fuse them together (potentially while incorporating information from the semantics) into a single 3D model.
...@@ -18,6 +20,8 @@ We provide the following data for the challenge: ...@@ -18,6 +20,8 @@ We provide the following data for the challenge:
* A set of synthetic testing sequences consisting of calibrated images with their camera poses. * A set of synthetic testing sequences consisting of calibrated images with their camera poses.
* A set of real validation sequences consisting of calibrated images with their camera poses. * A set of real validation sequences consisting of calibrated images with their camera poses.
For a detailed discussion of the workshop challenge, please read our [ECCV paper](http://openaccess.thecvf.com/content_ECCVW_2018/papers/11131/Tylecek_The_Second_Workshop_on_3D_Reconstruction_Meets_Semantics_Challenge_Results_ECCVW_2018_paper.pdf)
## Data ## Data
### Download ### Download
...@@ -191,7 +195,8 @@ Please report any errors via [issue tracker](https://gitlab.inf.ed.ac.uk/3DRMS/C ...@@ -191,7 +195,8 @@ Please report any errors via [issue tracker](https://gitlab.inf.ed.ac.uk/3DRMS/C
Production of this dataset was supported by EU project TrimBot2020. Production of this dataset was supported by EU project TrimBot2020.
Please cite the following paper when using the dataset: Please cite the following [paper](http://openaccess.thecvf.com/content_ECCVW_2018/papers/11131/Tylecek_The_Second_Workshop_on_3D_Reconstruction_Meets_Semantics_Challenge_Results_ECCVW_2018_paper.pdf)
when using the dataset:
@techreport{tylecek2018rms, @techreport{tylecek2018rms,
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