| # EventActivityNet Dataset Generation |
|
|
| ## Source Video Lineage |
|
|
| Both representations were generated from the non-interpolated/original-rate |
| ActivityNet video lineage. Source frame rate varies by video, no source video is |
| resampled or interpolated, and source spatial resolution is preserved. |
|
|
| ## Large Subset Curation |
|
|
| The canonical Large set contains 3,263 unique videos. The recovered curation |
| implementation: |
|
|
| - merged ActivityNet Captions train and validation metadata before sampling; |
| - used seed `2025`; |
| - used initial class-balanced sampling with `max(5, int(class_ratio * class_count))` and `class_ratio=0.2`; |
| - used 33% and 66% duration quantiles; |
| - enriched event-friendly examples using caption keywords or first-frame darkness. |
|
|
| The keyword list is `run`, `fast`, `sprint`, `night`, `dark`, and |
| `slow-motion`; the darkness rule is normalized first-frame mean brightness |
| below `0.4`. |
|
|
| ## HDF5 Generation |
|
|
| The recovered implementation follows: |
|
|
| 1. `activitynet.py` video loading; |
| 2. `mp4_to_h5.mp4_to_h5_stream()`; |
| 3. `EventEmulatorGPU.video_to_voxel()`; |
| 4. temporal grouping; |
| 5. HDF5 writing. |
|
|
| | Parameter | 5-bin | 9-bin | |
| |---|---:|---:| |
| | `num_bins` | 5 | 9 | |
| | `frames_per_bin` | 1 | 1 | |
| | Source resizing | none | none | |
| | `events` dtype | `int16` | `int16` | |
| | Start/count dtypes | `int64` / `int32` | `int64` / `int32` | |
| | Event compression | gzip+shuffle | gzip+shuffle | |
| | Auxiliary compression | LZF+shuffle | LZF+shuffle | |
| | Learned checkpoint | none | none | |
|
|
| The canonical 9-bin lineage was generated with a frozen deterministic |
| configuration using RNG seed `42`. The emulator creates and seeds its generator |
| for each streaming batch while carrying the previous frame and returned |
| potential across batches. This is recorded as technical reproducibility |
| metadata; it is not a comparative quality claim. |
|
|
| ## Generic Grouping Semantics |
|
|
| For bin count `B` and `N` decoded source frames: |
|
|
| ```text |
| T_B = ceil((N - 1) / B) |
| ``` |
|
|
| Each generated event slice represents one adjacent-frame transition. |
| `events[t]` groups up to `B` consecutive slices; |
| `voxel_event_start[t] = B*t`; and `voxel_event_count[t]` records the valid |
| slice count. The final group is zero-filled beyond its valid count. |
|
|
| ## Timing Basis |
|
|
| Seconds-level conversion uses each video's released rational nominal or average |
| frame rate. Construction follows decoded frame order and does not consume |
| per-frame presentation timestamps, so mapping is approximate for |
| within-video variable-frame-rate streams. No fixed 25-fps or 240-fps assumption |
| should be used. |
|
|
| ## Release Scales |
|
|
| Large is the recovered historical set. Medium and Small are deterministic |
| nested v1.0 scales selected with seed `2025` and strata |
| `(split, class_label, duration_bucket, event_friendly)`. Small is a strict |
| subset of Medium, and Medium is a strict subset of Large. Both event voxel |
| representations share these scale manifests. |
|
|
| ## Validation |
|
|
| Final validation confirmed exactly 3,263 readable files per representation, |
| the same 2,316/947 split assignment, expected tensor length and metadata arrays, |
| and zero remaining structural failures. Canonical HDF5 payload sizes are |
| 4,355,745,895,245 bytes for 5-bin and 4,214,122,096,103 bytes for 9-bin. |
|
|
