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I noticed an inconsistency regarding the test set splitting for the M3D-Seg dataset between the paper and the dataset's README on Hugging Face.
In the paper, it is stated:
"In M3D-Seg, 20% of the data from AbdomenCT-1K [42], Totalsegmnetator [66], and CT-Organ [53] is allocated as the test set for both semantic segmentation and referring expression segmentation."
Thank you for your attention.
Both statements are correct. We split all segmentation datasets into training and testing sets with an 8:2 ratio, consistent with SegVol. However, due to space limitations in the paper, we report the results of some datasets, such as AbdomenCT-1K, Totalsegmnetator, and CT-Organ. We welcome you to compare with us on any dataset using the same split, not limited to the three datasets presented in the paper.
Hello @baifanxxx,
I noticed an inconsistency regarding the test set splitting for the M3D-Seg dataset between the paper and the dataset's README on Hugging Face.
In the paper, it is stated:
However, in the Hugging Face README, it mentions:
Could you please clarify which data splitting method is correct? How can I reproduce the results as reported in the paper?
Thank you for your assistance.
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