The RSR and RPR are inconsistent with your results. Could you upload your metrics evaluation code?

[wshku]

Using your code of test.py and test dataset of FE240hz and VisEvent, I get your tracking results. Then I use the metrics evaluation code from the VisEvent project, https://github.com/wangxiao5791509/VisEvent_SOT_Benchmark, to evaluate your STNet's performance. I went through the VisEvent code and it is fine.

Here are my results:
FE240hz: RSR 60.3%, RPR 82.3%,
VisEvent: RSR 26.3%, RPR 49.9%,

some of which are inferior to your claimed results in the paper:
FE240hz: RSR 58.5%, RPR 89.6%.
VisEvent: RSR 35.5%, RPR 49.2%.

STNet seems not to outperform the counterpart methods. I am wondering whether you could provide your evaluation code

[laisimiao]

@Jee-King Could you provide your raw results on FE240hz and VisEvent so that we can evaluate them directly on their toolkits?

[Jee-King]

Thank you for pointing it out. We evaluate all trackers by following pytracking.
We checked the checkpoint.pth we uploaded, and the performance on FE240hz is: RSR 60.2%, RPR 87.9%.
In fact, the uploaded checkpoint in GitHub is slightly different from the camera-ready version. For example, only 48 non-rigid sequences in the Visevent are used for testing in this code, but 172 sequences are used for testing in our camera-ready.
Therefore, there is a gap in the results on VisEvent.
You can download our raw results of the paper from here. You can also see all the VisEvent test sequences we use.