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jayleicn / moment_detr

[NeurIPS 2021] Moment-DETR code and QVHighlights dataset
https://arxiv.org/abs/2107.09609
MIT License
259 stars 44 forks source link

Meaning of GT saliency scores #16

Closed QinghongLin closed 2 years ago

QinghongLin commented 2 years ago

Thank you for your great work and open-source code.

I have an issue with the GT saliency scores (only localized 2-sec clips), can you please explain briefly? besides, how Predicted saliency scores (for all 2-sec clip) corresponds to the previous term?

Thanks!

Best, Kevin

Build models...
Loading feature extractors...
Loading CLIP models
Loading trained Moment-DETR model...
Run prediction...
------------------------------idx0
>> query: Chef makes pizza and cuts it up.
>> video_path: run_on_video/example/RoripwjYFp8_60.0_210.0.mp4
>> GT moments: [[106, 122]]
>> Predicted moments ([start_in_seconds, end_in_seconds, score]): [
    [49.967, 64.9129, 0.9421], 
    [66.4396, 81.0731, 0.9271], 
    [105.9434, 122.0372, 0.9234], 
    [93.2057, 103.3713, 0.2222], 
    ..., 
    [45.3834, 52.2183, 0.0005]
   ]
>> GT saliency scores (only localized 2-sec clips):  # what it means?
    [[2, 3, 3], [2, 3, 3], ...]
>> Predicted saliency scores (for all 2-sec clip):  # how this correspond to the GT saliency scores?
    [-0.9258, -0.8115, -0.7598, ..., 0.0739, 0.1068]
QinghongLin commented 2 years ago

Thanks, I have found the answers here.