Comments (4)
WingsBrokenAngel
commented on May 28, 2024
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(1)-(4) is right. msrvtt_tag_gt_4_msvd.npy is generated by using 300 words from the MSVD dataset to label the MSR-VTT dataset.
msvd_tag_gt_4_msvd.npy and msrvtt_tag_gt_4_msvd.npy are used to train a semantic detection network for MSVD dataset.msvd_tag_gt_4_msrvtt.npy and msrvtt_tag_gt_4_msrvtt.npy are used to train a semantic detection network for MSR-VTT dataset. -
deploy.prototxt is provided in the original repository (There is a hyper-link in README).
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The average pooling operation is performed along the time axis.
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The file that is eco+resnext is named as eco_res and the one that is resnext+eco is named as res_eco.
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AndyMjw
commented on May 28, 2024
very useful，thank you.
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AndyMjw
commented on May 28, 2024
sorry,I can not find “deploy.prototxt” link in READMe,only ECO_full_kinetics.caffemodel link there,can you provide one,thank you.
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WingsBrokenAngel
commented on May 28, 2024
You can find it in the ECO's source code: https://github.com/mzolfaghari/ECO-efficient-video-understanding .
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Related Issues (15)
- msrvtt_resnext_eco feats HOT 2
- If the test set is used for training tag_net? HOT 1
- Nan Values Generated by the tagging network HOT 1
- about semantic detection network generate meaningful semantic features for videos HOT 1
- Tagging checkpoint
- About test
- ECO features
- How to generate these pkl file in the Data Section? HOT 2
- Question about MSR-VTT. HOT 5
- implementation detail HOT 1
- 请问sentence length loss在代码中体现在哪里 HOT 3
- 您好，请问增加candidate tags的数量是否还会提高指标？ HOT 1
- how to get close mAP as the newer version 《A Semantics-Assisted Video Captioning Model Trained with Scheduled Sampling》 HOT 1
- Dataset Split
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