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Inconsistency between reported metric and self-trained results #60

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seanzhuh opened this issue Jul 29, 2024 · 2 comments
Open

Inconsistency between reported metric and self-trained results #60

seanzhuh opened this issue Jul 29, 2024 · 2 comments

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@seanzhuh
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Hi, I've traiend on waldo_kitchen of LERF dataset using your code but the reproduced result (Loc. Acc is 0.8182) was lower than that reported in your paper (0.955). What could be the reason?

@garrisonz
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garrisonz commented Nov 15, 2024

More result for reference.

I train and eval on teatime of LERF dataset follow README instruction, using the default parameter.

  self-trained in paper
mIoU scores 58.0 65.1
Localization accuracy 83.1 88.1

@AbdallahElsayed73
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I personally trained on Teatime dataset and I got 88.1 localization accuracy. The only difference I found with self-training was indeed the evaluation on Waldo Kitchen although I got 77.3% localization accuracy. I also got accuracy of 67.6% on ramen dataset while it was reported to be 73.2% in the paper

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