NazirNayal8 / RbA

Official code for RbA: Segmenting Unknown Regions Rejected by All (ICCV 2023)
https://kuis-ai.github.io/RbA/
MIT License
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Different quantitive results between the paper and the leaderboard on SMIYC dataset #14

Closed cuttle-fish-my closed 1 month ago

cuttle-fish-my commented 3 months ago

Hi, thanks to your effort on this fantastic work! I notice that the quantitive results of SMIYC dataset in paper is as following:

image

But in the leaderboard of SMIYC, the results of Rba has been boosted significantly(see the following figures):

image image

I'm wondering where did the improvements come from? Have you updated the results with RbA + Mapillary + COCO Outlier Supervision?

Thanks in advance and looks forward to your replay!

NazirNayal8 commented 1 month ago

Greetings @cuttle-fish-my ,

Thank you for you interest in our work. The results on the SMIYC benchmark are for the models trained using mapillary as additional training data. We added a table in the paper that shows these results in the supplementary:

https://openaccess.thecvf.com/content/ICCV2023/supplemental/Nayal_RbA_Segmenting_Unknown_ICCV_2023_supplemental.pdf

cuttle-fish-my commented 1 month ago

Thanks!