Closed yanghhx closed 3 years ago
Hey, I don't get you completely. There might be an intermediate epoch that results in a higher accuracy and a lower loss. However, I decided to report the results for the final epoch.
Or doesn't the approach train at all? Can you post a log and a screenshot of the tensorboard output?
I have solved the problem. Thanks for your reply.
At 2021-10-26 14:08:11, "Raphael Memmesheimer" @.***> wrote:
Hey, I don't get you completely. There might be an intermediate epoch that results in a higher accuracy and a lower loss. However, I decided to report the results for the final epoch.
Or doesn't you approach train at all? Can you post a log and a screenshot of the tensorboard output?
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Dear Doctor, I have read your two papers and related codes,Skeleton-DML: Deep Metric Learning for Skeleton-Based One-Shot Action Recognition and SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition. I have found the codes of them are very similar. I'm very interested in one-shot acition recognition based on skeleton and your works.Could you please tell me the difference? I'm very grateful if you reply to me.
At 2021-10-30 16:28:10, "Raphael Memmesheimer" @.***> wrote:
Closed #3.
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You are right, the papers follow a similar approach with a different focus. SL-DML aims at generalizing across different modalities (inertial, skeleton, inter-modal) and proposes one-shot action recognition by employing metric learning. Skeleton-DML actually builds on the SL-DML idea but focuses on improving for skeleton-based action recognition with a much more in-depth ablation study on skeleton-data using different skeleton-based representations (also a new representation is suggested, that we found to perform better in our experiments). We actually also compare against SL-DML in the Skeleton-DML paper. In that case just the representation differs.
The main differences are in the representation and the mining of the samples.
SL-DML representation
Skeleton-DML representation
Hope this helps. If you have further questions, I'm happy to answer them.
Thanks for your reply. I think I need to study more deeply.
At 2021-11-09 23:24:02, "Raphael Memmesheimer" @.***> wrote:
You are right, the papers follow a similar approach with a different focus. SL-DML aims at generalizing across different modalities (inertial, skeleton, inter-modal) and proposes one-shot action recognition by employing metric learning. Skeleton-DML actually builds on the SL-DML idea but focuses on improving for skeleton-based action recognition with a much more in-depth ablation study on skeleton-data using different skeleton-based representations (also a new representation is suggested, that we found to perform better in our experiments). We actually also compare against SL-DML in the Skeleton-DML paper. In that case just the representation differs.
The main differences are in the representation and the mining of the samples.
SL-DML representation
Skeleton-DML representation
Hope this helps. If you have further questions, I'm happy to answer them.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or unsubscribe. Triage notifications on the go with GitHub Mobile for iOS or Android.
I have trained the network 100 epoch, but the best accuracy and the loss are not improved. Could you tell me how to solve it?