Some questions in your paper about wtal-uncertainty-modeling HOT 6 CLOSED

Hello, thanks for your interest!
I hope the replies below would help.

1. Density in Fig. 2 indicates the portion of samples, e.g., the value of 0.008 in density means 0.8 % of the samples are located there. It plays the exactly same role as normalization, which is necessary as the amounts of action and background frames are quite different.
2. Yes, you're right.
3. Yes, it is. To clarify more, the softmax score uses the first term (softmax score) in Eq. 3.
4. In fact, the softmax score is unrelated to the feature magnitudes, as they are never used. On the other hand, suppose the case where fusion score is used without uncertainty modeling loss. As you mentioned, the magnitudes are not separated, so we need to perform min-max normalization rather than using m. Therefore, it should be "the second".
5. For some reason, we put the ActivityNet features on hold. They may be released after the conference. We are sorry for the delay.

If you have further questions, feel free to let me know.
Thanks!

from wtal-uncertainty-modeling.

Thanks for your reply!

from wtal-uncertainty-modeling.

Hello, thanks for your interest!
I hope the replies below would help.

1. Density in Fig. 2 indicates the portion of samples, e.g., the value of 0.008 in density means 0.8 % of the samples are located there. It plays the exactly same role as normalization, which is necessary as the amounts of action and background frames are quite different.
2. Yes, you're right.
3. Yes, it is. To clarify more, the softmax score uses the first term (softmax score) in Eq. 3.
4. In fact, the softmax score is unrelated to the feature magnitudes, as they are never used. On the other hand, suppose the case where fusion score is used without uncertainty modeling loss. As you mentioned, the magnitudes are not separated, so we need to perform min-max normalization rather than using m. Therefore, it should be "the second".
5. For some reason, we put the ActivityNet features on hold. They may be released after the conference. We are sorry for the delay.

If you have further questions, feel free to let me know.
Thanks!

@Pilhyeon Could you please tell me that if there are also videos are excluded during training or testing in ActivityNet v1.2 or v1.3?

from wtal-uncertainty-modeling.

Hello, thanks for your interest!
I hope the replies below would help.

1. Density in Fig. 2 indicates the portion of samples, e.g., the value of 0.008 in density means 0.8 % of the samples are located there. It plays the exactly same role as normalization, which is necessary as the amounts of action and background frames are quite different.
2. Yes, you're right.
3. Yes, it is. To clarify more, the softmax score uses the first term (softmax score) in Eq. 3.
4. In fact, the softmax score is unrelated to the feature magnitudes, as they are never used. On the other hand, suppose the case where fusion score is used without uncertainty modeling loss. As you mentioned, the magnitudes are not separated, so we need to perform min-max normalization rather than using m. Therefore, it should be "the second".
5. For some reason, we put the ActivityNet features on hold. They may be released after the conference. We are sorry for the delay.

If you have further questions, feel free to let me know.
Thanks!

@Pilhyeon Could you please tell me that if there are also videos are excluded during training or testing in ActivityNet v1.2 or v1.3?

Can you reproduce the result by training the model in your environment by yourself not using the pre-trained model ?

from wtal-uncertainty-modeling.

@mitming In fact, some of the ActivityNet videos are unavailable at this time, so the entries of training/validation videos used for experiments are slightly different depending on the papers. In our case, 9,272 training videos and 4,541 validation videos were available.

from wtal-uncertainty-modeling.

Hello, thanks for your interest!
I hope the replies below would help.

1. Density in Fig. 2 indicates the portion of samples, e.g., the value of 0.008 in density means 0.8 % of the samples are located there. It plays the exactly same role as normalization, which is necessary as the amounts of action and background frames are quite different.
2. Yes, you're right.
3. Yes, it is. To clarify more, the softmax score uses the first term (softmax score) in Eq. 3.
4. In fact, the softmax score is unrelated to the feature magnitudes, as they are never used. On the other hand, suppose the case where fusion score is used without uncertainty modeling loss. As you mentioned, the magnitudes are not separated, so we need to perform min-max normalization rather than using m. Therefore, it should be "the second".
5. For some reason, we put the ActivityNet features on hold. They may be released after the conference. We are sorry for the delay.

If you have further questions, feel free to let me know.
Thanks!

@Pilhyeon Could you please tell me that if there are also videos are excluded during training or testing in ActivityNet v1.2 or v1.3?

Can you reproduce the result by training the model in your environment by yourself not using the pre-trained model ?

Sorry, I have tried many times, but I still cannot reproduce the result in paper without pre-trained model, could you reproduce it?

from wtal-uncertainty-modeling.