Comments (2)
Did you just transfer these gt mask into unified taxonomy of
194 classes using NaiveTaxonomyConverter?
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Hi @lxtGH, please refer to section 3.2 of our paper:
"We re-annotate only the datasets used for learning, leaving the evaluation datasets intact."
We did this for fair comparison with other results on these established benchmarks. Indeed, we were the runner-up at the 2020 Robust Vision Challenge that used several of these benchmarks.
Regarding how to project results in the universal taxonomy into a test dataset's taxonomy, please refer to the section entitled "Using the MSeg taxonomy on a held-out dataset." of our paper on page 6. We discuss this in detail.
from mseg-api.
Related Issues (19)
- Really Nice Work! HOT 1
- Repeated entries for WildDash HOT 2
- MSEG CamVid test set: is listed but not remapped? HOT 2
- Where is supplement mentioned in the paper HOT 4
- Thank you for your nice work HOT 1
- Can't download ADE20K_2016_07_26.zip HOT 3
- Reintroducing the crosswalk class back into MSeg HOT 2
- Problem with COCOPanoptic dataset HOT 8
- BDD dataset info HOT 7
- Mapillary dataset HOT 5
- code, data and trained models HOT 3
- Trying to reduce the number of classes of Mseg
- Invitation of making PR about dataset on MMSegmentation. HOT 1
- Can't find supplement mentioned in paper HOT 2
- Final taxonomy HOT 1
- Does MSEG dupport a CPU-only mode?
- Error in dataset path verification HOT 26
- WildDash download and extraction scripts HOT 3
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