Comments (1)
Hello. Thanks for your interest in our paper.
We apologize for the inconvenience.
Actually, it is our mistake to report the results for the validation set.
Performances for the test set are as below. Will be updated in the paper.
We again apologize for the inconvenience. Thank you.
[email protected] | [email protected] | [email protected] | mIoU | |
---|---|---|---|---|
Val set | 52.23 | 39.61 | 22.23 | 36.48 |
Test set | 54.36 | 39.47 | 23.44 | 37.42 |
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Related Issues (11)
- About the timing of releasing implementation codes HOT 2
- About the paper HOT 4
- 你好,感谢您的工作,根据您开源的代码程序和数据,我进行了复现,qvhighlights训练的val ,有些指标还是差异比较大的 HOT 3
- About Dummy Tokens. HOT 5
- Questions about some details? HOT 1
- Moment-adaptive Saliency Token Generator: Cross-Attention HOT 1
- Unable to reproduce the experimental results in your paper HOT 3
- Question about pre-training HOT 1
- Failed to find metrics for "QVHighlights only CLIP" model. HOT 1
- Customized dataset feature extraction in Charades-STA style HOT 8
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