alabnii/sciclaimeval-shared-task huggingface dataset:
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Method & Training Data & K400 & MiT & SSv2 & ActNet \\ \hline
\fancyname & \begin{tabular}[c]{@{}l@{}}(e),(f),(g),(h) \end{tabular} & 81.9 / 95.2 & 41.7 / 71.0 & 68.9 / 91.6 & 87.4 / 97.3 \\ \hline \hline
Vanilla (50 ep) & \begin{tabular}[c]{@{}l@{}}(e),(f), (g),(h) \end{tabular} & 80.1/ 94.0 & 33.4 / 60.1 & 60.8 / 89.0 & 86.5 / 97.1 \\ \hline
Vanilla (200 ep) & \begin{tabular}[c]{@{}l@{}}(e),(f), (g),(h) \end{tabular} & 80.6 / 94.7 & 35.1 / 63.9 & 56.8 / 85.3 & 86.3 / 97.2 \\ \hline
w/o Informative Loss & \begin{tabular}[c]{@{}l@{}}(e),(f),(g),(h) \end{tabular} & 13.5 / 33.4 & 7.3 / 19.9 & 9.7 / 28.5 & 24.8 / 54.3 \\ \hline
\begin{tabular}[c]{@{}l@{}}w/o Informative Loss \\ \& w/o Projection Add\end{tabular} & \begin{tabular}[c]{@{}l@{}}(e),(f),(g),(h) \end{tabular} & 80.4 / 94.5 & 41.7 / 71.0 & 68.9 / 91.6 & 86.5 / 97.4 \\ \hline
w/o Projection Loss & \begin{tabular}[c]{@{}l@{}}(e),(f),(g),(h) \end{tabular} & 80.6 / 94.8	& 41.7 / 71.0 & 68.9 / 91.6	& 86.9 / 97.5 \\ \hline
w/o ActNet & (e),(f),(g) & 81.4 / 95.0	& 41.3 / 70.5 & 68.7 / 91.3	& - \\ \hline
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\caption{Table 3: Ablation experiments. We investigate the effectiveness of each component of our method as well as compare to vanilla multi-dataset training method.
``Vanilla'' means using cross entropy (CE) loss in training.
``w/o informative los'' means using CE and projection loss.
The numbers are top-1/top-5 accuracy, respectively.
Training data:
(e) Kinetics-400;
(f) SSv2;
(g) MiT;
(h) ActivityNet.}
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