Comments (3)
Thanks for your interest on our work.
I suppose the first evaluation result you showed is generated using the mai_city_block.ply
file in the gt_models
folder. This is the model used for simulation in Carla and there's a shift between the model's and the point cloud's coordinate system. It's the reason why the evaluation results seem to be completely wrong.
We used the gt_map_pc_mai.ply
point cloud file as the reference, which should be corresponding to the second evaluation result you showed. The difference between what you showed and what we reported in the paper is caused by different parameter settings. In the paper, different from the default parameter setting in the open source config file, we used the 10cm leaf_vox_size
, 50m pc_radius_m
and with ekional loss on. Additionally, as mentioned in the paper, we use a fairer accuracy metric by taking the ground truth point cloud masked by the intersection of the reconstructed meshes of all the compared methods.
The reconstructed mesh and the cropped intersection reference point cloud can be downloaded from here. You can use them to get the similar results as reported in our paper.
Thanks.
from shine_mapping.
Hi, I run your evaluation code using the meshes you provided. And I get the great results.
This is using gt_map_pc_mai.ply as the reference.
And this is using the cropped intersection reference as the reference.
The results are better than the paper results. But I still wonder why it is not same as paper results. Is it effected by the version of open3d or any other thing?
In my conda env , the version of open3d is 0.10.0.0
from shine_mapping.
I know the computation of evaluation metrics have some randonness, and the result is right. Sorry to bother.
from shine_mapping.
Related Issues (20)
- Other dataset config file HOT 1
- If need to know the pose of each frame in advance during real-time operation? HOT 1
- what shuold I do to make this program run all frame on mai_city sequence 00? HOT 2
- Just point cloud, no LiDAR point, Can a map be made? HOT 3
- MapVisualizer is always stucked when visualizing the incremental mapping process? HOT 1
- semantic loss HOT 2
- Tuning shine HOT 7
- Color results of rendered images HOT 1
- each leaf node store multiple points? HOT 3
- Weird about the calculation of free space uniform sampling ? HOT 2
- Colored Mesh HOT 3
- how to compute completion? HOT 2
- Noise results testing on the nuScenes dataset HOT 7
- Question on the sdf map HOT 3
- some question about the metric accuracy? HOT 6
- how to train the freezed decoder (pre-trained) on a new dataset? HOT 1
- How did you refine the pose of the Newer College Dataset? HOT 2
- The boosting time consumption of incremental shine-mapping on seq00 from MaiCity with 700 > pc_count_gpu_limit HOT 1
- How to compute the signed reconstruction error? HOT 2
- Problem when trying to run the script HOT 3
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from shine_mapping.