| | --- |
| | dataset_info: |
| | features: |
| | - name: vclip_id |
| | dtype: string |
| | - name: question_id |
| | dtype: int64 |
| | - name: question |
| | dtype: string |
| | - name: answer |
| | dtype: string |
| | - name: frame_indexes |
| | sequence: int64 |
| | - name: choices |
| | struct: |
| | - name: A |
| | dtype: string |
| | - name: B |
| | dtype: string |
| | - name: C |
| | dtype: string |
| | - name: D |
| | dtype: string |
| | - name: E |
| | dtype: string |
| | - name: video_metadata |
| | struct: |
| | - name: CLIP-reference-interval-clip |
| | sequence: float64 |
| | - name: CLIP-reference-interval-video |
| | sequence: float64 |
| | - name: bitrate |
| | dtype: int64 |
| | - name: codec |
| | dtype: string |
| | - name: frame_dimensions |
| | sequence: int64 |
| | - name: frame_dimensions_resized |
| | sequence: int64 |
| | - name: frame_rate |
| | dtype: float64 |
| | - name: resolution |
| | dtype: string |
| | - name: resolution_resized |
| | dtype: string |
| | - name: vclip_duration |
| | dtype: float64 |
| | - name: vclip_frame_count |
| | dtype: int64 |
| | - name: vclip_interval_in_video |
| | sequence: float64 |
| | - name: video_duration |
| | dtype: float64 |
| | - name: video_frame_count |
| | dtype: int64 |
| | - name: video_id |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 5358616 |
| | num_examples: 11218 |
| | - name: test |
| | num_bytes: 1977870 |
| | num_examples: 3874 |
| | download_size: 2168577 |
| | dataset_size: 7336486 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: data/train-* |
| | - split: test |
| | path: data/test-* |
| | --- |
| | |
| | <h1 align='center' style="text-align:center; font-weight:bold; font-size:2.0em;letter-spacing:2.0px;"> |
| | LV-Haystack: Temporal Search for Long-Form Video Understanding</h1> |
| | |
| |
|
| | <p align='center' style="text-align:center;font-size:1.1em;"> |
| | <a href="https://jhuiye.com/" target="_blank">Jinhui Ye<sup>1</sup></a>, |
| | <a href="https://zihanwang314.github.io/" target="_blank">Zihan Wang<sup>2</sup></a>, |
| | <a href="https://haosensun.github.io/" target="_blank">Haosen Sun<sup>2</sup></a>, |
| | <a href="https://keshik6.github.io/" target="_blank">Keshigeyan Chandrasegaran<sup>1</sup></a>, <br> |
| | <a href="https://zanedurante.github.io/" target="_blank">Zane Durante<sup>1</sup></a>, |
| | <a href="https://ceyzaguirre4.github.io/" target="_blank">Cristobal Eyzaguirre<sup>1</sup></a>, |
| | <a href="https://talkingtorobots.com/yonatanbisk.html" target="_blank">Yonatan Bisk<sup>3</sup></a>, |
| | <a href="https://www.niebles.net/" target="_blank">Juan Carlos Niebles<sup>1</sup></a>, |
| | <a href="https://profiles.stanford.edu/ehsan-adeli" target="_blank">Ehsan Adeli<sup>1</sup></a>, <br> |
| | <a href="https://profiles.stanford.edu/fei-fei-li/" target="_blank">Li Fei-Fei<sup>1</sup></a>, |
| | <a href="https://jiajunwu.com/" target="_blank">Jiajun Wu<sup>1</sup></a>, |
| | <a href="https://limanling.github.io/" target="_blank">Manling Li<sup>2</sup></a><br/> |
| | Stanford University<sup>1</sup>, Northwestern University<sup>2</sup>, Carnegie Mellon University<sup>3</sup><br/> |
| | <a align='center' style="text-decoration: none; color: gray"> |
| | Dataset is part of the <a href="">T* project</a> |
| | <br/> |
| | <a href="https://examplewebsite.com" title="Website" target="_blank" rel="nofollow" style="text-decoration: none;">🌎Website</a> | |
| | <a href="https://examplecode.com" title="Dataset" target="_blank" rel="nofollow" style="text-decoration: none;">🧑💻Code</a> | |
| | <a href="https://arxiv.org/examplepaper" title="aXiv" target="_blank" rel="nofollow" style="text-decoration: none;">📄arXiv</a> | |
| | <a href="https://exampleleaderboard.com" title="Leaderboard" target="_blank" rel="nofollow" style="text-decoration: none;">🏆 Leaderboard (Coming Soon)</a><br> |
| | </p> |
| |
|
| | <img src="assets/img/logo.png" alt="Logo" width="400" height="auto" style="display:block; margin:auto;" /> |
| |
|
| | <p align=center> |
| |
|
| | </p> |
| |
|
| |
|
| |
|
| |
|
| |
|
| | #### Dataset Sample |
| |
|
| | ```python |
| | { |
| | 'vclip_id': '6338b73e-393f-4d37-b278-68703b45908c', |
| | 'question_id': 10, |
| | 'question': 'What nail did I pull out?', |
| | 'answer': 'E', |
| | 'frame_indexes': [5036, 5232], # the keyframe indexes |
| | 'choices': { |
| | 'A': 'The nail from the front wheel fender', |
| | 'B': 'The nail from the motorcycle battery compartment', |
| | 'C': 'The nail from the left side of the motorcycle seat', |
| | 'D': 'The nail from the rearview mirror mount', |
| | 'E': 'The nail on the right side of the motorcycle exhaust pipe' |
| | }, |
| | 'video_metadata': { |
| | '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]) |
| | '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. |
| | '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 |
| | 'frame_count': 14155, # Total number of frames in the video |
| | 'frame_rate': 30.0, # Frame rate of the video |
| | 'duration': 471.8333435058594, # Duration of the video that are valid and unbroken, in seconds |
| | 'resolution': '454x256', # Original resolution of the video |
| | 'frame_dimensions': None, # Frame dimensions (if available) |
| | 'codec': 'N/A', # Codec used for the video (if available) |
| | 'bitrate': 0, # Bitrate of the video (if available) |
| | 'frame_dimensions_resized': [340, 256], # Resized frame dimensions |
| | 'resolution_resized': '340x256', # Resized resolution |
| | 'video_id': 'b6ae365a-dd70-42c4-90d6-e0351778d991' # Unique video identifier |
| | } |
| | } |
| | ``` |
| |
|
| |
|
| | #### Dataset exploration |
| |
|
| | add hyperlink to demo |
| |
|
| | #### Dataset Usage |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | dataset = load_dataset("LVHaystack/LongVideoHaystack") |
| | print(dataset) |
| | ``` |
| | ```bash |
| | >>> DatasetDict({ |
| | train: Dataset({ |
| | features: ['vclip_id', 'question_id', 'question', 'answer', 'frame_indexes', 'choices', 'video_metadata'], |
| | num_rows: 11218 |
| | }) |
| | test: Dataset({ |
| | features: ['vclip_id', 'question_id', 'question', 'answer', 'frame_indexes', 'choices', 'video_metadata'], |
| | num_rows: 3874 |
| | }) |
| | }) |
| | ``` |
| |
|
| | #### Video Source Download |
| |
|
| | TODO: We plan to provide a script of how to download a subset from [Ego4d](https://ego4d-data.org/). |
| | 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: |
| | ```bash |
| | pip install ego4d |
| | |
| | ego4d --output_directory=your_path/videos/ \ |
| | --datasets full_scale annotations \ |
| | --metadata \ |
| | --video_uid_file video_uids.txt |
| | |
| | python process_videos_to_clips.py # TODO |
| | ``` |
| | 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: |
| |
|
| | ```python |
| | import datasets |
| | metadata = datasets.load_dataset("LVHaystack/LongVideoHaystack-metadata")["metadata"] |
| | with open("video_uids.txt", "w") as file: |
| | for video_id in list(set(metadata['video_id'])): |
| | file.write(video_id + " ") |
| | ``` |
| |
|
| | then, you need to transform them to video clips: |
| | ```python |
| | ``` |
| |
|
| |
|
| |
|
| | #### Dataset Statistics Summary |
| |
|
| | | **Metric** | **Total** | **Train** | **Test** | |
| | |-------------------------------|--------------|-------------|-------------| |
| | | **Video Statistics** | | | | |
| | | Total Videos | **988** | **744** | **244** | |
| | | Total Video Duration (hr) | 423.3 | 322.2 | 101.0 | |
| | | Avg. Video Duration (min) | 25.7 | 26.0 | 24.8 | |
| | | **Clip Statistics** | | | | |
| | | Total Video Clips | **1,324** | **996** | **328** | |
| | | Total Video Clip Duration (hr) | 180.4 | 135.3 | 45.0 | |
| | | Avg. Video Clip Duration (sec) | 8.2 | 8.2 | 8.2 | |
| | | **Frame Statistics** | | | | |
| | | Total Frames (k) | **45,700** | **34,800** | **10,900** | |
| | | Avg. Frames per Video (k) | 46.3 | 46.8 | 44.7 | |
| | | Ratio of Keyframe / Frame (‰) | 0.62 | 0.59 | 0.71 | |
| | | **QA Statistics** | | | | |
| | | Total QA Pairs | **15,092** | **11,218** | **3,874** | |
| | | Avg. QA Pair per Video | 15.3 | 15.1 | 15.9 | |
| | | Avg. QA Pair per Clip | 11.4 | 11.3 | 11.8 | |
| | | Avg. Keyframes per Question | 1.88 | 1.84 | 2.01 | |
| |
|
| |
|
| | #### Evaluation scripts |
| |
|
| | Please refer to [./eval.py](https://huggingface.co/datasets/LVHaystack/LongVideoHaystack/blob/main/eval.py). |
| |
|
| |
|
| |
|
| | #### Contact |
| | - Jinhui Ye: jinhuiyes@gmail.com |
| | - Zihan Wang: zihanw@u.northwestern.edu (datasets) |
| | - Haosen Sun: haosensun2026@u.northwestern.edu |
| | - Keshigeyan Chandrasegaran: keshik@stanford.edu |
| | - Manling Li: manling.li@northwestern.edu |
| |
|
| | #### Citation |
| |
|
| | ```bibtex |
| | @misc{tstar, |
| | title={Re-thinking Temporal Search for Long-Form Video Understanding}, |
| | 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}, |
| | year={2025}, |
| | eprint={2501.TODO}, |
| | archivePrefix={arXiv}, |
| | primaryClass={cs.LG} |
| | } |
| | ``` |
| | Website template borrowed from [HourVideo](https://huggingface.co/datasets/HourVideo/HourVideo). |
| |
|
