MMTrail is a large-scale multi-modality video-language dataset with over 20M trailer clips, featuring high-quality multimodal captions that integrate context, visual frames, and background music, aiming to enhance cross-modality studies and fine-grained multimodal-language model training. In short, we provided 2M+ LLaVA Video captions, 2M+ Music captions, and 60M+ Coca frame captions for 27.1khrs of Trailer videos.
| Split | Download | # Samples | Video Duration | Storage Space |
|---|---|---|---|---|
| Training-Coca | Download | 20M | 27.1 khrs | ~8.0 TB |
| Training | Download | 2.1M | 8.2 khrs | ~1.6 TB |
| Training( 2M Merge Caption) | TODO | 2.1M | 8.2 khrs | ~1.6 TB |
| Test (2M(sample 1w)) | Download. | 2.1M | 8.2 khrs | ~1.6 TB |
| Test | TODO (2.77 MB) | 1,000 | 3.5 hrs | 794 Mb |
- Release CCBY subset.
- Merge the data cleaning pipeline to this repo(Ongoing...).
- adding video dataset script
- Release MMTrail-20M metadata
- Release MMTrail-2M metadata
- 【2024/07/30】 We published 2M and 20M caption data files for download.
- 【2024/06/10】 We build our GitHub page
[
{
'video_id': 'zW1-6V_cN8I', # Video ID in MMTrail
'video_path': 'group_32/zW1-6V_cN8I.mp4', # Relative path of the dataset root path
'video_duration': 1645.52, # Duration of the video
'video_resolution': [720, 1280],
'video_fps': 25.0,
'clip_id': 'zW1-6V_cN8I_0000141', # Clip ID
'clip_path': 'video_dataset_32/zW1-6V_cN8I_0000141.mp4', # Relative path of the dataset root path
'clip_duration': 9.92, # Duration of the clip itself
'clip_start_end_idx': [27102, 27350], # Start frame_id and end frame_id
'image_quality': 45.510545094807945, # Image quality score
'of_score': 6.993135, # Optical flow score
'aesthetic_score': [4.515582084655762, 4.1147027015686035, 3.796849250793457],
'music_caption_wo_vocal': [{'text': 'This song features a drum machine playing a simple beat. A siren sound is played on the low register. Then, a synth plays a descending lick and the other voice starts rapping. This is followed by a descending run. The mid range of the instruments cannot be heard. This song can be played in a meditation center.', 'time': '0:00-10:00'}], # Music description of the background music without vocal (human voice).
'vocal_caption': 'I was just wondering...' # Speech recongitation.
'frame_caption': ['two people are standing in a room under an umbrella . ', 'a woman in a purple robe standing in front of a man . ', 'a man and a woman dressed in satin robes . '], # Coca caption of three key frame
'music_caption': [{'text': 'This music is instrumental. The tempo is medium with a synthesiser arrangement and digital drumming with a lot of vibrato and static. The music is loud, emphatic, youthful, groovy, energetic and pulsating. This music is a Electro Trap.', 'time': '0:00-10:00'}] # Music description of the background music.
'objects': [' bed', 'Woman', ' wall', ' pink robe', ' pillow'],
'background': 'Bedroom',
'ocr_score': 0.0,
'caption': 'The video shows a woman in a pink robe standing in a room with a bed and a table, captured in a series of keyframes that show her in various poses and expressions.', # Caption generation from LLaVA and rewrite by LLAMA-13B
'polish_caption': 'A woman in a pink robe poses and expresses herself in various ways in a room with a bed and a table, capturing her graceful movements and emotive facial expressions.', # Polished caption generation from LLaVA and rewrite by LLAMA-13B
'merge_caption': 'In a cozy bedroom setting, a stunning woman adorned in a pink robe gracefully poses and expresses herself, her movements and facial expressions captured in a series of intimate moments. The scene is set against the backdrop of a comfortable bed and a table, with an umbrella standing in a corner of the room. The video features two people standing together under the umbrella, a woman in a purple robe standing confidently in front of a man, and a man and woman dressed in satin robes, all set to an energetic and pulsating electro trap beat with a synthesiser arrangement and digital drumming. The music is loud and emphatic, capturing the youthful and groovy vibe of the video.'# The final description of the video. It is the merge of all above captions, and merged by LLaMA
}
}
]
The published version code is still under development.
Please refer to https://github.com/litwellchi/lvm_datapipe
The video samples are collected from a publicly available dataset. Users must follow the related license to use these video samples. We provide on the caption files.
@misc{chi2024mmtrailmultimodaltrailervideo,
title={MMTrail: A Multimodal Trailer Video Dataset with Language and Music Descriptions},
author={Xiaowei Chi and Yatian Wang and Aosong Cheng and Pengjun Fang and Zeyue Tian and Yingqing He and Zhaoyang Liu and Xingqun Qi and Jiahao Pan and Rongyu Zhang and Mengfei Li and Ruibin Yuan and Yanbing Jiang and Wei Xue and Wenhan Luo and Qifeng Chen and Shanghang Zhang and Qifeng Liu and Yike Guo},
year={2024},
eprint={2407.20962},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2407.20962},
}