Buckets:
| 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. | |
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