| --- |
| pretty_name: EventActivityNet |
| tags: |
| - event-based-vision |
| - video-understanding |
| - activitynet |
| - hdf5 |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # EventActivityNet v1.0 |
|
|
| EventActivityNet is a generated event voxel tensor dataset derived from |
| ActivityNet videos together with ActivityNet Captions annotations. It provides |
| two alternative temporal groupings over the same canonical 3,263-video set. |
| These are generated tensors, not native event-camera recordings. |
|
|
| | Representation | Public path | Videos | Train / validation | Shards (train / validation) | Event shape | Canonical HDF5 bytes | |
| |---|---|---:|---:|---:|---|---:| |
| | 5-bin | `data_5bin/` | 3,263 | 2,316 / 947 | 157 / 62 | `(T5, 5, H, W)` | 4,355,745,895,245 | |
| | 9-bin | `data_9bin/` | 3,263 | 2,316 / 947 | 157 / 62 | `(T9, 9, H, W)` | 4,214,122,096,103 | |
|
|
| The repository contains approximately 8.57 TB of tar-packaged payload. The |
| representations use identical video membership, split assignment, and shard |
| membership. Neither representation is presented as inherently better than the |
| other. |
|
|
| ## Dataset Structure |
|
|
| Each ActivityNet video corresponds to exactly one HDF5 member in each |
| representation. Train/validation and Large/Medium/Small membership are defined |
| by manifests; the nested scales do not duplicate payload files. |
|
|
| ```text |
| data_5bin/{train,validation}/ |
| data_9bin/{train,validation}/ |
| metadata/{5bin,9bin}/ |
| metadata/video_metadata.jsonl |
| annotations/ |
| scales/ |
| docs/ |
| ``` |
|
|
| ## Data Format |
|
|
| Every HDF5 file contains exactly: |
|
|
| - `events`: `(T_B, B, H, W)`, `int16`; |
| - `voxel_event_start`: `(T_B,)`, `int64`; |
| - `voxel_event_count`: `(T_B,)`, `int32`. |
|
|
| Here `B` is 5 or 9. For `N` decoded source frames: |
|
|
| ```text |
| T_B = ceil((N - 1) / B) |
| ``` |
|
|
| Each event slice represents one adjacent decoded-frame transition. An |
| `events[t]` tensor groups up to `B` consecutive transition slices. The final |
| group may be partial; unused bins are zero-filled. Timing uses each video's |
| released rational source FPS metadata. |
|
|
| See [Dataset Format](docs/DATASET_FORMAT.md) for schema, timing, and memory-safe |
| loading details. |
|
|
| ## Release Scales |
|
|
| | Scale | Videos | Hours | Train | Validation | Classes | Event-friendly | |
| |---|---:|---:|---:|---:|---:|---:| |
| | Large | 3,263 | 106.94 | 2,316 | 947 | 200 | 65.31% | |
| | Medium | 1,537 | 50.00 | 1,074 | 463 | 200 | 64.80% | |
| | Small | 667 | 20.00 | 473 | 194 | 200 | 64.62% | |
|
|
| Small is a strict subset of Medium, and Medium is a strict subset of Large. |
|
|
| ## Included Metadata |
|
|
| - `annotations/activitynet_captions.json`: timestamped ActivityNet Captions descriptions; |
| - `annotations/activitynet_actions.json`: ActivityNet v1.3 temporal actions; |
| - `annotations/eventactivitynet_alignment.json`: derived caption/action alignment; |
| - `annotations/annotation_issues.jsonl`: known source annotation quirks; |
| - `metadata/video_metadata.jsonl`: shared original-rate timing metadata and per-representation tensor metadata; |
| - `metadata/5bin/` and `metadata/9bin/`: representation-specific shard manifests, summaries, and checksums; |
| - `scales/`: Large, Medium, and Small manifests and public statistics. |
|
|
| ## Intended Uses |
|
|
| The dataset supports research on generated event voxel representation learning, |
| activity recognition, caption-aligned activity modeling, and comparison across |
| nested dataset scales or temporal groupings. |
|
|
| It is out of scope for identifying people, biometric recognition, surveillance |
| deployment, or consequential decisions about individuals. |
|
|
| ## Limitations |
|
|
| - The event voxel tensors are generated from conventional videos rather than recorded by an event camera. |
| - Source FPS and spatial resolution vary by video. |
| - Timing is based on decoded frame order and released rational nominal or average FPS; per-frame presentation timestamps are not consumed. |
| - The subset is curated rather than an unbiased conversion of all ActivityNet videos. |
|
|
| ## Checksums |
|
|
| ```bash |
| sha256sum -c metadata/5bin/shard_checksums.sha256 |
| sha256sum -c metadata/9bin/shard_checksums.sha256 |
| ``` |
|
|
| ## Documentation |
|
|
| - [Dataset Card](docs/DATASET_CARD.md) |
| - [Dataset Format](docs/DATASET_FORMAT.md) |
| - [Dataset Generation](docs/DATASET_GENERATION.md) |
| - [Release Notes](docs/RELEASE_NOTES.md) |
| - [License Notes](docs/LICENSE_NOTES.md) |
|
|
| ## Licensing and Citation |
|
|
| ActivityNet and ActivityNet Captions source terms, licenses, citation |
| obligations, and redistribution restrictions still apply. See |
| [License Notes](docs/LICENSE_NOTES.md) and [CITATION.cff](CITATION.cff). |
|
|
| ## Release Status |
|
|
| Both complete representations passed final integrity and remote-layout audits. |
| The public payload contains 438 tar shards: 219 per representation. |
|
|
