ZJULearning / RMI

This is the code for the NeurIPS 2019 paper Region Mutual Information Loss for Semantic Segmentation.

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

About setting of baseline

zhizhangxian opened this issue · comments

Hi,your work is so amazing and help me a lot!
I mentioned in your reported result in paper, you did some comparison between deeplab and your results on different datasets, but I ran your code with batch size=16, deeplab v3+ model , resnet101 backbone on VOC2012 dataset, but only get 0.772miou after about 30k iterations(just the default setting), so can you tell me how can I set the hyper-parameters to get the desire result (including 78.8 with crossentropy loss and higer miou with your proposed loss)?
this is my result on val dataset:
image
Thank you very much for your excellent work!

Glad to hear that our work can benefit someone.

In fact, 78.8% is the data report in the official paper, i.e., the DeepLabv3+ paper.
Our reimplementation result is 78.17% with DeepLabv3+ (batch_size=16, output_stride=16).
During my experiments, I also had some similar results as you with DeepLabv3+.
So I do not have many tricks to help you.

But you may find something helpful in this paper https://arxiv.org/abs/1812.01187.
It helped me a lot when I took my experiments.

Thanks very much!