![Samples from Flickr30k dataset (Image credit: "https://bryanplummer.com/Flickr30kEntities/").](imgs/msrvtt.png)

# MSRVTT Dataset (Retrieval)

## Description
[MSRVTT](https://www.microsoft.com/en-us/research/publication/msr-vtt-a-large-video-description-dataset-for-bridging-video-and-language/) dataset is a large-scale video benchmark for video understanding, especially the emerging task of translating video to text. This is achieved by collecting 257 popular queries from a commercial video search engine, with 118 videos for each query. In its current version, MSR-VTT provides 10K web video clips with 41.2 hours and 200K clip-sentence pairs in total. Each clip is annotated with about 20 natural sentences by 1,327 AMT workers.

## Task
Cross modal retrieval: (1) **video-text**: given a video as query, retrieve texts from a gallery; (2) **text-video**: given a text as query, retrieval videos from a gallery.


## Metrics
Common metrics are recall@k, denotes the [recall score](https://en.wikipedia.org/wiki/Precision_and_recall) after k retrieval efforts.

We use TR to denote the video-text retrieval recall score and VR to denote text-video retrieval score.

## Leaderboard
(Ranked by TR@1.)
<!-- | Rank | Model  | TR@1  | TR@5  | TR@10 | IR@1  | IR@5  | IR@10 |                                                                                                                   Resources                                                                                                                    |
| ---- | :----: | :---: | :---: | :---: | :---: | :---: | :---: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| 1    |  BLIP  | 82.4  | 95.4  | 97.9  | 65.1  | 86.3  | 91.8  | [paper](https://arxiv.org/pdf/2201.12086.pdf), [code](https://github.com/salesforce/BLIP), [demo](https://huggingface.co/spaces/Salesforce/BLIP), [blog](https://blog.salesforceairesearch.com/blip-bootstrapping-language-image-pretraining/) | -->

## References
Xu, Jun, Tao Mei, Ting Yao, and Yong Rui. "Msr-vtt: A large video description dataset for bridging video and language." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 5288-5296. 2016.