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--- |
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dataset_info: |
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features: |
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- name: vclip_id |
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dtype: string |
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- name: question_id |
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dtype: int64 |
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- name: question |
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dtype: string |
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- name: answer |
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dtype: string |
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- name: frame_indexes |
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sequence: int64 |
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- name: choices |
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struct: |
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- name: A |
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dtype: string |
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- name: B |
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dtype: string |
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- name: C |
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dtype: string |
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- name: D |
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dtype: string |
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- name: E |
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dtype: string |
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- name: video_metadata |
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struct: |
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- name: CLIP-reference-interval-clip |
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sequence: float64 |
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- name: CLIP-reference-interval-video |
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sequence: float64 |
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- name: bitrate |
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dtype: int64 |
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- name: codec |
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dtype: string |
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- name: frame_dimensions |
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sequence: int64 |
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- name: frame_dimensions_resized |
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sequence: int64 |
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- name: frame_rate |
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dtype: float64 |
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- name: resolution |
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dtype: string |
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- name: resolution_resized |
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dtype: string |
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- name: vclip_duration |
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dtype: float64 |
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- name: vclip_frame_count |
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dtype: int64 |
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- name: vclip_interval_in_video |
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sequence: float64 |
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- name: video_duration |
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dtype: float64 |
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- name: video_frame_count |
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dtype: int64 |
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- name: video_id |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 5358616 |
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num_examples: 11218 |
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- name: test |
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num_bytes: 1977870 |
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num_examples: 3874 |
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download_size: 2168577 |
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dataset_size: 7336486 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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--- |
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<h1 align='center' style="text-align:center; font-weight:bold; font-size:2.0em;letter-spacing:2.0px;"> |
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LV-Haystack: Temporal Search for Long-Form Video Understanding</h1> |
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<p align='center' style="text-align:center;font-size:1.1em;"> |
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<a href="https://jhuiye.com/" target="_blank">Jinhui Ye<sup>1</sup></a>, |
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<a href="https://zihanwang314.github.io/" target="_blank">Zihan Wang<sup>2</sup></a>, |
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<a href="https://haosensun.github.io/" target="_blank">Haosen Sun<sup>2</sup></a>, |
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<a href="https://keshik6.github.io/" target="_blank">Keshigeyan Chandrasegaran<sup>1</sup></a>, <br> |
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<a href="https://zanedurante.github.io/" target="_blank">Zane Durante<sup>1</sup></a>, |
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<a href="https://ceyzaguirre4.github.io/" target="_blank">Cristobal Eyzaguirre<sup>1</sup></a>, |
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<a href="https://talkingtorobots.com/yonatanbisk.html" target="_blank">Yonatan Bisk<sup>3</sup></a>, |
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<a href="https://www.niebles.net/" target="_blank">Juan Carlos Niebles<sup>1</sup></a>, |
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<a href="https://profiles.stanford.edu/ehsan-adeli" target="_blank">Ehsan Adeli<sup>1</sup></a>, <br> |
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<a href="https://profiles.stanford.edu/fei-fei-li/" target="_blank">Li Fei-Fei<sup>1</sup></a>, |
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<a href="https://jiajunwu.com/" target="_blank">Jiajun Wu<sup>1</sup></a>, |
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<a href="https://limanling.github.io/" target="_blank">Manling Li<sup>2</sup></a><br/> |
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Stanford University<sup>1</sup>, Northwestern University<sup>2</sup>, Carnegie Mellon University<sup>3</sup><br/> |
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<a align='center' style="text-decoration: none; color: gray"> |
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Dataset is part of the <a href="">T* project</a> |
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<br/> |
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<a href="https://examplewebsite.com" title="Website" target="_blank" rel="nofollow" style="text-decoration: none;">🌎Website</a> | |
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<a href="https://examplecode.com" title="Dataset" target="_blank" rel="nofollow" style="text-decoration: none;">🧑💻Code</a> | |
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<a href="https://arxiv.org/examplepaper" title="aXiv" target="_blank" rel="nofollow" style="text-decoration: none;">📄arXiv</a> | |
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<a href="https://exampleleaderboard.com" title="Leaderboard" target="_blank" rel="nofollow" style="text-decoration: none;">🏆 Leaderboard (Coming Soon)</a><br> |
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</p> |
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<img src="assets/img/logo.png" alt="Logo" width="400" height="auto" style="display:block; margin:auto;" /> |
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<p align=center> |
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</p> |
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#### Dataset Sample |
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```python |
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{ |
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'vclip_id': '6338b73e-393f-4d37-b278-68703b45908c', |
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'question_id': 10, |
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'question': 'What nail did I pull out?', |
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'answer': 'E', |
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'frame_indexes': [5036, 5232], # the keyframe indexes |
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'choices': { |
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'A': 'The nail from the front wheel fender', |
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'B': 'The nail from the motorcycle battery compartment', |
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'C': 'The nail from the left side of the motorcycle seat', |
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'D': 'The nail from the rearview mirror mount', |
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'E': 'The nail on the right side of the motorcycle exhaust pipe' |
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}, |
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'video_metadata': { |
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'CLIP-reference-interval-vclip': [180.0, 240.0], # Time interval of the "vclip" that is considered to be important by CLIP. this is calculated by (CLIP-reference-interval-video - vclip-interval-in-video[0]) |
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'CLIP-reference-interval-video': [180.0, 240.0], # Time interval of the "video" that is considered to be important by CLIP. This is originally from the **Ego4D dataset**, used in our work for annotators to quickly locate in the video. |
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'vclip_interval_in_video': [0.0, 480.06667277018227], # the vclip start and end second, i.e., for [a, b], the vclip starts at the a second of the video, ends at the b second of the video |
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'frame_count': 14155, # Total number of frames in the video |
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'frame_rate': 30.0, # Frame rate of the video |
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'duration': 471.8333435058594, # Duration of the video that are valid and unbroken, in seconds |
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'resolution': '454x256', # Original resolution of the video |
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'frame_dimensions': None, # Frame dimensions (if available) |
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'codec': 'N/A', # Codec used for the video (if available) |
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'bitrate': 0, # Bitrate of the video (if available) |
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'frame_dimensions_resized': [340, 256], # Resized frame dimensions |
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'resolution_resized': '340x256', # Resized resolution |
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'video_id': 'b6ae365a-dd70-42c4-90d6-e0351778d991' # Unique video identifier |
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} |
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} |
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``` |
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#### Dataset exploration |
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add hyperlink to demo |
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#### Dataset Usage |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("LVHaystack/LongVideoHaystack") |
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print(dataset) |
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``` |
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```bash |
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>>> DatasetDict({ |
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train: Dataset({ |
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features: ['vclip_id', 'question_id', 'question', 'answer', 'frame_indexes', 'choices', 'video_metadata'], |
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num_rows: 11218 |
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}) |
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test: Dataset({ |
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features: ['vclip_id', 'question_id', 'question', 'answer', 'frame_indexes', 'choices', 'video_metadata'], |
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num_rows: 3874 |
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}) |
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}) |
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``` |
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#### Video Source Download |
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TODO: We plan to provide a script of how to download a subset from [Ego4d](https://ego4d-data.org/). |
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For now, you can refer to their official guide [here](https://github.com/facebookresearch/Ego4d/tree/main/ego4d/cli). Your code would be look like the follows: |
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```bash |
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pip install ego4d |
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ego4d --output_directory=your_path/videos/ \ |
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--datasets full_scale annotations \ |
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--metadata \ |
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--video_uid_file video_uids.txt |
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python process_videos_to_clips.py # TODO |
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``` |
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Please find [video_uid.txt](https://huggingface.co/datasets/LVHaystack/LongVideoHaystack/blob/main/video_uid.txt) in our repo, or you can generate it by: |
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```python |
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import datasets |
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metadata = datasets.load_dataset("LVHaystack/LongVideoHaystack-metadata")["metadata"] |
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with open("video_uids.txt", "w") as file: |
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for video_id in list(set(metadata['video_id'])): |
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file.write(video_id + " ") |
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``` |
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then, you need to transform them to video clips: |
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```python |
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``` |
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#### Dataset Statistics Summary |
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| **Metric** | **Total** | **Train** | **Test** | |
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|-------------------------------|--------------|-------------|-------------| |
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| **Video Statistics** | | | | |
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| Total Videos | **988** | **744** | **244** | |
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| Total Video Duration (hr) | 423.3 | 322.2 | 101.0 | |
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| Avg. Video Duration (min) | 25.7 | 26.0 | 24.8 | |
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| **Clip Statistics** | | | | |
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| Total Video Clips | **1,324** | **996** | **328** | |
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| Total Video Clip Duration (hr) | 180.4 | 135.3 | 45.0 | |
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| Avg. Video Clip Duration (sec) | 8.2 | 8.2 | 8.2 | |
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| **Frame Statistics** | | | | |
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| Total Frames (k) | **45,700** | **34,800** | **10,900** | |
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| Avg. Frames per Video (k) | 46.3 | 46.8 | 44.7 | |
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| Ratio of Keyframe / Frame (‰) | 0.62 | 0.59 | 0.71 | |
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| **QA Statistics** | | | | |
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| Total QA Pairs | **15,092** | **11,218** | **3,874** | |
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| Avg. QA Pair per Video | 15.3 | 15.1 | 15.9 | |
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| Avg. QA Pair per Clip | 11.4 | 11.3 | 11.8 | |
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| Avg. Keyframes per Question | 1.88 | 1.84 | 2.01 | |
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#### Evaluation scripts |
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Please refer to [./eval.py](https://huggingface.co/datasets/LVHaystack/LongVideoHaystack/blob/main/eval.py). |
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#### Contact |
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- Jinhui Ye: [email protected] |
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- Zihan Wang: [email protected] (datasets) |
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- Haosen Sun: [email protected] |
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- Keshigeyan Chandrasegaran: [email protected] |
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- Manling Li: [email protected] |
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#### Citation |
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```bibtex |
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@misc{tstar, |
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title={Re-thinking Temporal Search for Long-Form Video Understanding}, |
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author={Jinhui Ye and Zihan Wang and Haosen Sun and Keshigeyan Chandrasegaran and Zane Durante and Cristobal Eyzaguirre and Yonatan Bisk and Juan Carlos Niebles and Ehsan Adeli and Li Fei-Fei and Jiajun Wu and Manling Li}, |
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year={2025}, |
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eprint={2501.TODO}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.LG} |
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} |
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``` |
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Website template borrowed from [HourVideo](https://huggingface.co/datasets/HourVideo/HourVideo). |
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