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Original file line number | Diff line number | Diff line change |
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@@ -1,10 +1,25 @@ | ||
Dataset Min. per-class samples Max. per-class samples | ||
------------ --------------------------------------- ------------------------------------------- | ||
$\ \ \many \ \ \medium \ \ \few\ $ $\ \ \ \many \ \ \ \medium \ \ \ \few\ $ | ||
<!-- --> | ||
ImageNet‑LT $\ 101 \q 20 \q 5\ $ $1,280 \q 100 \q 19\ $ | ||
Places‑LT $\ 103 \q 20 \q 5\ $ $4,980 \q 100 \q 19\ $ | ||
CIFAR‑100‑LT $\ 102 \q 20 \q 5\ $ $\ph{,0}500 \q \ph{0}98 \q 19\ $ | ||
iNaturalist $\ 101 \q 20 \q 2\ $ $1,000 \q 100 \q 19\ $ | ||
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: Minimum and maximum per-class training samples for long-tailed datasets. {#tbl:dataset_splits} | ||
\hypertarget{tbl:dataset_splits}{} | ||
\begin{table} | ||
\centering | ||
\begin{tabular}{@{}lrrrcrrr@{}} | ||
\toprule | ||
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\multirow{2}*{Dataset} & | ||
\multicolumn{3}{c}{Min. class samples} && | ||
\multicolumn{3}{c}{Max. class samples} \\ | ||
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\cmidrule{2-4} \cmidrule{6-8} | ||
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& many & med. & few && many & med. & few \\ | ||
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\midrule | ||
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ImageNet‑LT & 101 & 20 & 5 && 1,280 & 100 & 19 \\ | ||
Places‑LT & 103 & 20 & 5 && 4,980 & 100 & 19 \\ | ||
CIFAR‑100‑LT & 102 & 20 & 5 && 500 & 98 & 19 \\ | ||
iNaturalist & 101 & 20 & 2 && 1,000 & 100 & 19 \\ | ||
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\bottomrule | ||
\end{tabular} | ||
\caption{Minimum and maximum per-class training samples for long-tailed datasets.\label{tbl:dataset_splits}} | ||
\end{table} |
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Dataset \ \ \ \ \ Samples \ \ \ \ \ Classes \ \ \ \ \ \ \ \ \ Train samples | ||
------------ ------------------------------------------- ------------------------------------------------------------------ -------------------------------------------------- | ||
$\qq \train \qq \val \qq \test$ $\q\ \total \q \many\ \ \q \medium \q \few$ $\qq \many\ \ \q \medium \q \ \ \few$ | ||
<!-- --> | ||
ImageNet‑LT $\qq 115,846 \q 20,000 \q 50,000$ $\qq 1,000 \q 385 \q \ph{,0}479 \q 136\ph{,0}$ $\qq \ph{0}88,693 \q 25,510 \q 1,643\ph{0}$ | ||
Places‑LT $\qq \ph{0}62,500 \q \ph{0}7,300 \q 36,500$ $\qq 365\ph{,0} \q 131 \q \ph{,0}163 \q 71\ph{0,0}$ $\qq \ph{0}52,762 \q \ph{0}8,934 \q 804\ph{0,0}$ | ||
CIFAR‑100‑LT $\qq \ph{0}10,847 \q \ph{00,000} \q 10,000$ $\qq 100\ph{,0} \q \ph{0}35 \q \ph{0,0}35 \q 30\ph{0,0}$ $\qq \ph{00}8,824 \q \ph{0}1,718 \q 305\ph{0,0}$ | ||
iNaturalist $\qq 437,513 \q \ph{00,000} \q 24,426$ $\qq 8,142 \q 842 \q 4,076 \q 3,224$ $\qq 258,340 \q 133,061 \q 46,112$ | ||
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: Statistics of long-tailed datasets. {#tbl:dataset_stats} | ||
\hypertarget{tbl:dataset_stats}{} | ||
\begin{table} | ||
\centering | ||
\begin{tabular}{@{}lrrrclrrrcrrr@{}} | ||
\toprule | ||
|
||
\multirow{2}*{Dataset} & | ||
\multicolumn{3}{c}{Samples} && | ||
\multicolumn{4}{c}{Classes} && | ||
\multicolumn{3}{c}{Train samples} \\ | ||
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\cmidrule{2-4} \cmidrule{6-9} \cmidrule{11-13} | ||
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& train & val & test && total & many & med. & few && many & med. & few \\ | ||
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\midrule | ||
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ImageNet‑LT & 115,846 & 20,000 & 50,000 && 1,000 & 385 & 479 & 136 && 88,693 & 25,510 & 1,643 \\ | ||
Places‑LT & 62,500 & 7,300 & 36,500 && 365 & 131 & 163 & 71 && 52,762 & 8,934 & 804 \\ | ||
CIFAR‑100‑LT & 10,847 & - & 10,000 && 100 & 35 & 35 & 30 && 8,824 & 1,718 & 305 \\ | ||
iNaturalist & 437,513 & - & 24,426 && 8,142 & 842 & 4,076 & 3,224 && 258,340 & 133,061 & 46,112 \\ | ||
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\bottomrule | ||
\end{tabular} | ||
\caption{Statistics of long-tailed datasets.\label{tbl:dataset_stats}} | ||
\end{table} |
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