Comments (3)
I have done the following two experiments: one is to delete semantic information (reduce the dimension to five dimensions) and preserve virtual point coordinates (preserve virt_point2); Another method is to preserve semantic information (preserve virt_points1) and delete virtual points (delete virt_point2). The result of the second method is much better than that of the first method. It seems that semantic information can improve the performance of the CenterPoint more than more virtual point.
from mvp.
-
yes
-
I think the first approach won't work (and will degrade the performance). Basically, we can't just remove the semantic information as the model won't be able to distinguish virtual and real points in that stage, which hurts the localization accuracy.
It's true that semantic information improves the detection the most, but our focus here is that adding virtual points (as well as their semantic information and confidence score) can help more with the localization at long range (table 4)
from mvp.
Thank you very much!
from mvp.
Related Issues (20)
- Generating results on nuscenes test set HOT 2
- MaskFormer pretrained on coco-panoptic HOT 1
- MVP reproduction on NuScenes with OpenPCDet (mAP:64.22 NDS:68.96) HOT 6
- Where is the difference between creating data with or without virtual point? HOT 1
- Missing sweeps virtual points HOT 2
- Doubts about virtual_lidar_points HOT 1
- semantic information different between PointPainting and MVP HOT 3
- Can it be applied to the waymo dataset? HOT 3
- Sorry
- Generage `data/nuScenes/infos_train_10sweeps_withvelo_filter_painted_True.pkl` file HOT 3
- what is the shape of the virtual points dimension? HOT 6
- generate the points HOT 1
- Is there an online implementation of MVP? HOT 1
- Visualization HOT 2
- generate the virtual points HOT 1
- questions
- some issues about process of generate virtual points HOT 1
- Some details about generating virtual points
- good job!! l really like it
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 mvp.