Retrieval on MSVD

[sharontaozi]

I am sorry to bother you again, because I am doing some experiments on the MSVD about retrieval. But I have some troubles and I want to ask you these questions:

1. The number of descriptions corresponding to each video on MSVD is different. How to deal with this part in the experiment (such as: What is the number of descriptions corresponding to each video on training , test, verification?Or other processing details)
2. The paper said that Otani's processing method is to randomly select 5 sentences for each test video. But I read Xu's paper 《Joint Modeling Deep Video and Compositional text to bridge vision and language in a unified framework》. It wrote: Firstly, for each testing video we select 5 sentences, so totally we have 3350 sentences and 670 videos. So, what is the difference between these two of processing?
   I really want to know how to deal with MSVD.Thank you very much!

[danieljf24]

Sorry for the late reply. We used all the sentences for training, validation, and testing.

[xixiareone]

I would like to ask you a question: in the MSVD data set, especially in the test phase, do you evaluate all sentences, or just randomly select 5 sentences from the MSVD for evaluation?

[xixiareone]

很抱歉再次打扰您，因为我正在MSVD上进行一些有关检索的实验。但是我有一些麻烦，我想问你以下问题：

1. 与MSVD上的每个视频相对应的描述数量是不同的。在实验中如何处理这一部分（例如：与每个视频有关的培训，测试，验证或其他处理细节对应的描述数量是多少？）
2. 文章说，大谷的处理方法是为每个测试视频随机选择5个句子。但是我读过徐的论文《联合建模深度视频和合成文本以在统一框架中桥接视觉和语言》。它写道：首先，对于每个测试视频，我们选择5个句子，因此总共有3350个句子和670个视频。那么，这两种处理之间有什么区别？
   我真的很想知道如何处理MSVD。非常感谢！

I would like to ask you a question: in the MSVD data set, especially in the test phase, do you evaluate all sentences, or just randomly select 5 sentences from the MSVD for evaluation?

[danieljf24]

In the previous version of our w2vv paper, in Table 5, we used all the corresponding sentences instead of randomly sampled 5 sentences for each test video ( Results using data partition from Xu et al. [40]). For the results using data partition from Otani et al. [24], we used 5 sentences for each test video provided by Otani et al, while all the training sentences.