| --- |
| dataset_info: |
| features: |
| - name: video_id |
| dtype: string |
| - name: vclip_id |
| dtype: string |
| - name: question |
| dtype: string |
| - name: options |
| struct: |
| - name: A |
| dtype: string |
| - name: B |
| dtype: string |
| - name: C |
| dtype: string |
| - name: D |
| dtype: string |
| - name: E |
| dtype: string |
| - name: answer |
| dtype: string |
| - name: frame_indexes_video |
| sequence: int64 |
| - name: frame_indexes_vclip |
| sequence: int64 |
| - 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: 6862627 |
| num_examples: 12892 |
| - name: val |
| num_bytes: 589648 |
| num_examples: 1000 |
| - name: test_tiny |
| num_bytes: 107818 |
| num_examples: 200 |
| - name: test |
| num_bytes: 528993 |
| num_examples: 1000 |
| download_size: 2374756 |
| dataset_size: 8089086 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: val |
| path: data/val-* |
| - split: test_tiny |
| path: data/test_tiny-* |
| - 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"> |
| <strong> CVPR 2025 </strong>. Dataset is part of the <a href="https://longvideohaystack.github.io/">T* project</a> |
| <br/> |
| <a href="https://longvideohaystack.github.io/" title="Website" target="_blank" rel="nofollow" style="text-decoration: none;">🌎Website</a> | |
| <a href="https://github.com/LongVideoHaystack/TStar" title="Dataset" target="_blank" rel="nofollow" style="text-decoration: none;">🧑💻Code</a> | |
| <a href="https://arxiv.org/abs/2504.02259" title="aXiv" target="_blank" rel="nofollow" style="text-decoration: none;">📄arXiv</a> | |
| <a href="" 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 |
| { |
| 'video_id': 'b6ae365a-dd70-42c4-90d6-e0351778d991', |
| 'vclip_id': '6338b73e-393f-4d37-b278-68703b45908c', |
| 'question_id': 10, |
| 'question': 'What nail did I pull out?', |
| 'answer': 'E', |
| 'frame_indexes_vclip': [5036, 5232], # the keyframe indexes in the vclip |
| 'frame_indexes_video': [5036, 5232], # the keyframe indexes in the video |
| '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['train']) |
| ``` |
| ```bash |
| Dataset({ |
| features: ['video_id', 'vclip_id', 'question', 'options', 'answer', 'frame_indexes_video', 'frame_indexes_vclip', 'video_metadata'], |
| num_rows: 12892 |
| }) |
| ``` |
|
|
| #### Download and Process Video Source |
|
|
| TODO: We plan to provide a script of how to download a subset from [Ego4d](https://ego4d-data.org/) and process them. |
| Below is download part adapted from their [official guide](https://github.com/facebookresearch/Ego4d/tree/main/ego4d/cli) and we will add video2clip script soon. |
| ```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_uids.txt](https://huggingface.co/datasets/LVHaystack/LongVideoHaystack/blob/main/video_uids.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 + " ") |
| ``` |
| To follow evaluation for LongVideoBench in our paper, please find script to transform LongVideoBench to LongVideoHaystack format in `transform_longvideobench.py`. |
|
|
|
|
| <!-- then, you need to transform them to video clips: |
| ```python |
| ``` --> |
|
|
|
|
|
|
| #### Dataset Statistics Summary |
|
|
| | **Metric** | **Total** | **Train** | **Val** | **Test** | **Test_Tiny** | |
| |-------------------------------|-----------|-----------|---------|----------|---------------| |
| |🎥 Video Statistics | | | | | | |
| | Total Videos | **988** | **858** | **71** | **53** | **13** | |
| | Total Video Duration (hr) | 420 | 370 | 27 | 24 | 4.3 | |
| | Avg. Video Duration (min) | 26 | 26 | 23 | 28 | 20 | |
| |🎞️ Clip Statistics | | | | | | |
| | Total Video Clips | **1,324** | **1,141** | **89** | **80** | **17** | |
| | Total Clip Duration (hr) | 180 | 160 | 12 | 11 | 2.2 | |
| | Avg. Clip Duration (sec) | 490 | 490 | 480 | 470 | 460 | |
| |🖼️ Frame Statistics | | | | | | |
| | Total Frames (k) | **45,716**| **40,150**| **2,958**| **2,637**| **467** | |
| | Avg. Frames per Video (k) | 46 | 47 | 42 | 50 | 36 | |
| | Ratio of Keyframe / Frame (‰) | 0.62 | 0.59 | 0.69 | 0.78 | 0.89 | |
| |❓ QA Statistics | | | | | | |
| | Total QA Pairs | **15,092**| **12,892**| **1,000**| **1,000**| **200** | |
| | Avg. QA Pairs per Video | 15 | 15 | 14 | 19 | 15 | |
| | Avg. QA Pairs per Clip | 11 | 11 | 11 | 13 | 12 | |
| | Avg. Keyframes per Question | 1.9 | 1.8 | 2.0 | 2.1 | 2.1 | |
| |
| |
| |
| #### 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 |
| - Anabella Aisaro: anabellaisaro2025@u.northwestern.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={2504.02259}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2504.02259}, |
| } |
| ``` |
| Website template borrowed from [HourVideo](https://huggingface.co/datasets/HourVideo/HourVideo). |
| |
