Comments (2)
the test scale factor can be any value. But since our model is trained on datasets whoes scale factor is sampled from 1 to 4, thus we donot show the performance on 8x or 16x (bigger than 4x).
However, the trained model still can test on 8x or 16x (bigger than 4x). My experiences tell me that
the performance is lower than that of the model trained on single scale factor (8x or 16x).
If you want to use the model for application where the scale factor s is bigger than 4x, i think it is better to retrain the model and scale factor is sampled from 1 or s ( s is the max scale factor). And you will get better results. Donot test the scale factor which is out of the traing scale factors range. any scale factor in the range of traing scale factors is ok.
In this paper, we mainly show the capacity of our model to solve non-integer scale factor and single model for any scale factor. And most SISR models only study the scale factor 2,3,4. That is why we donot test on 8x, 16x. That is the reason.
from meta-sr-pytorch.
Thanks for your reply.
By the way, Meta-SR is amazing works on super resolution!
from meta-sr-pytorch.
Related Issues (20)
- Have you debugged it yet?
- Meta-Upscale Module
- meta-upscale
- meta-upscale的输入
- 请问输入矩阵为什么需要mask
- Meta-upscale的实现 HOT 3
- RuntimeError: cuda runtime error (2) HOT 5
- Trying to train Meta-RCAN but failed HOT 2
- Testing directories HOT 3
- rewrite dataloader for more recnt Pytorch
- meta-learning for weight prediction
- dataloader error, help plz~
- Higher PSNR when i use pretrained model?
- 请问怎样运行 geberate_LR_metasr_X1_X4.m 文件?
- Pretrained models
- 如何将MetaUpSampler 改成适用于3d图像的上采样?
- 请问,想改成 针对3d数据,该怎么改? 比如(batch,C, h, w, d),超分到(batch, C, H, W, D)。 HOT 2
- 你好,能帮忙指点下吗? 改成3d 后 pos_mat_small 维度不是Scale x Scale x Scale x 3的维度? h_offset这需要改吗? HOT 3
- 你好,cols = nn.functional.unfold(up_x.permute(0, 2, 3, 1), self.kernel_size, padding=1),该咋改呀? HOT 1
- Pre-training model selection for testing
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 meta-sr-pytorch.