Comments (4)
Hi~
The main difference of OneNet and CenterNet are:
(1) As you mentions, OneNet is labeling without Gaussian pre-processing.
(2) CenterNet labels the positive sample as the feature point closest to center of gt box (only location cost), OneNet labels the positive samples by MinCost(sum of classification cost and location cost).
from onenet.
Hi,
Thank you. I see that in Fig. 5 of your paper.
Sorry that I am still unclear about that
OneNet labels the positive samples by MinCost(sum of classification cost and location cost).
because you should prepare the positive samples before getting MinCost.
Since your positive samples are more discriminative than center of gt box, how did you decide their positions?
Did you used technical methods like attention map, or just labeled them by human decisions ?
from onenet.
Hi,
Thank you. I see that in Fig. 5 of your paper.
Sorry that I am still unclear about thatOneNet labels the positive samples by MinCost(sum of classification cost and location cost).
because you should prepare the positive samples before getting MinCost.
Since your positive samples are more discriminative than center of gt box, how did you decide their positions?
Did you used technical methods like attention map, or just labeled them by human decisions ?
The positive samples are decided by MinCost, instead of human annotations.
from onenet.
Hi,
I still cannot understand how to calculate the sum of classification cost and location cost of each pixel ?
from onenet.
Related Issues (20)
- util/box_ops.py 尝试过diou,ciou、? HOT 1
- Hi. Have you ever tried using SGD? HOT 1
- why the large and medium object‘Ap is lower than the centernet‘s
- Pretrained weight and Sparse RCNN implementation HOT 2
- Cost and loss difference HOT 2
- What differences between min cost assignment in OneNet and Hungarian algorithm in Sparse R-CNN? HOT 2
- KeyError: 'Non-existent config key: MODEL.OneNet'
- Setting of learning rate HOT 2
- The loss is Nan HOT 3
- Hi!, when num_classes ==1, cant compute focal loss, because if p.shape[-1] ==self.num_classes: nn.init.constant_(p, self.bias_value) HOT 1
- It seems that there is a typo in table 5 . HOT 2
- Why is my accuracy at 1.441? HOT 2
- DLA34 Backbone Result HOT 1
- Why change the matcher from Minimum Cost to Hungarian? HOT 2
- Why does OneSeg performance drop? HOT 2
- 请问,有MMDetection实现吗? HOT 2
- Ablation on original training losses? HOT 3
- where are the multi-head training implement? HOT 2
- about the index of positive
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 onenet.