xhwxd / dbsn Goto Github PK
View Code? Open in Web Editor NEWUnpaired Learning of Deep Image Denoising
Unpaired Learning of Deep Image Denoising
Hi, it's glad to see such a creative work on unsupervised denoising area. And could you please offer the trained model for D-BSN?
Hi, in README you mentioned that
For D-BSN,we suggest to pre-train μ first by using L2 Loss, then pre-train σ_μ and σ_n by using the Pre-trained loss (./net/losses.py), finally fine-tune the whole framework.
In your .sh script I noticed the dataset for pre-training μ is actually synthetic data (by adding poisson-gaussian noise to the clean images). My question is, will D-BSN be degraded or improved if use real noisy dataset to pre-train μ?
Thanks.
Hi,
I met a problem when using "rgb_gaussian_nL50.pth" model. I entered "dbsn_color" folder and modified rgb_test.sh to
But there is an error occured like that:
So I traversed the key in "rgb_gaussian_nL50.pth" model, it shows:
It seems that a dtcn model is in this checkpoint. Could you help me run rgb_gaussian model? Thank you very much!
Hi, may I ask we need to pre-train only for the RGB image or both grey and RGB images all need pre-train μ first by using L2 Loss, then pre-train σ_μ and σ_n by using the Pre-trained loss ?
I am very interested in the actual effect of the paper. I tried to run rgb_test.sh, and the final result was a picture of synthesized noise. Can you provide a demo of denoising? gratitude
I wonder if we could have access to knowledge distillation code for rgb image? Thank you very much.
When I train the gray model, the loss becomes negative. It is very confusing.
Hi, when I used the provided pre-trained model with default arguments and code, I found that some parameters are not correct which leads to no corresponding parameters, e.g. rgb_gaussian_nL25.pth..
Thank you for any helpful suggestions!
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.