Closed yuheyuan closed 2 years ago
As reported in Table 3 of the paper, this is the expected behavior of our model (see the column of class train mIoU=0).
The difficulty on the class train comes from two sources:
There have been some techniques able to improve on the train class adaptation quality, you can read them if you are interested:
As reported in Table 3 of the paper, this is the expected behavior of our model (see the column of class train mIoU=0).
The difficulty on the class train comes from two sources:
- Some trains in Cityscapes dataset are actually tram (Example]. and there is no tram in the GTAV and SYNTHIA dataset. The appearance difference is larger because of the apperance difference between train and tram
- The train class is rare in both dataset, leading to class imbalance and training difficulty.
There have been some techniques able to improve on the train class adaptation quality, you can read them if you are interested:
- Our other work: Discussion on this issue in Section 5.1. Hoyer, L., Dai, D., Wang, Q., Chen, Y., & Van Gool, L. (2021). Improving semi-supervised and domain-adaptive semantic segmentation with self-supervised depth estimation. arXiv preprint arXiv:2108.12545.
- CBST, class-balanced training from Zou, Y., Yu, Z., Kumar, B. V. K., & Wang, J. (2018). Unsupervised domain adaptation for semantic segmentation via class-balanced self-training. In Proceedings of the European conference on computer vision (ECCV) (pp. 289-305).
thank you for your writing.I understand. Really thank you !
I download your pretrained model, and start demo But I find train iou 0.0
I train my model on it, and test eval_syn2city.py. Here are 3 classes Iou 0.0 because missing classed in source domain. but I download pretrained model ,and run eval_gta2city.sh still miss one class train. So, I want to know why. Is it may train class didn't appear city datasets? So it's IOU is 0.