---
license: cc-by-nc-4.0
pretty_name: VoxMem EPIC-KITCHENS share
tags: [egocentric, epic-kitchens, depth, camera-pose, video-qa]
---
# VoxMem EPIC-KITCHENS share

This share holds derived data of the VoxMem project, built from [EPIC-KITCHENS-100](https://epic-kitchens.github.io/).
The videos are (c) the EPIC-KITCHENS team under CC BY-NC 4.0, and this share keeps that license: it is for
non-commercial research. The original MP4s are not here.

**Current version: 2026-10-18 (v3).** It holds:
* the question set (frozen 2026-10-12), both tiers (accurate and rough), including the questions built with Gemini;
* one label row per question;
* the trainable lists;
* the token cache, 599 videos (the 572 of the previous version + 27 new ones, poses from EPIC-Fields only);
* the hand masks, the reference-frame tokens and their exact-frame 3D, and the fps table.

The voxels are not shared. The training machine builds them from the token cache with one script.

**To train, use the code, not this page:**
* the guide is `docs/TRAIN_ELSEWHERE_EPIC_V3.md` in the [VoxMem repo](https://github.com/tree1111/VoxMem), branch
  `hdepic-gen-epic-questions`;
* `bash scripts/kit/download_epic_v3.sh` downloads, checks and unpacks everything below into place.

Every path here is the path under the VoxMem data root (`src/voxmem/paths.py`), except the two `reftok-4b` /
`refgeo-4b` tars, which unpack into `<code>/results/cache/hdepic/`.

## v3 (2026-10-18)

| path | what |
|---|---|
| `epic-kitchens/tokens/qwen3vl-4b_512px/<video>.npz` | 599 files (3.43 TB), one per video. Each holds the Qwen3-VL-4B visual tokens (144 per 512x288 frame), similarity features, 3D points, camera pose, depth and the frame-rule table. Every frame is chosen by the frame rule: each wanted 1 fps frame exactly, else the nearest frame with a camera pose within +-0.5 s, else that second is dropped. sha256 in `epic-kitchens/tokens/tokens_MANIFEST.tsv` and `SHA256SUMS_tokens.txt`. |
| `epic-kitchens/questions/questions_2026-10-18.tar` | the question set: `2026-10-18/<type>/{accurate,rough}.jsonl` for 25 question types, plus `LIST.{csv,md}` (also loose as `LIST_2026-10-18.{csv,md}`: per type, its counts, whether Gemini was involved, its sources) and `reference_images.json` |
| `epic-kitchens/questions/labels_2026-10-18.jsonl` | one row per question. The main columns: `tier`, `gemini`, `split`, `coverage`, `n_frames`, `scene_id`, `voxel_tokens`, `est_tokens`, `trainable`, `reason` (the first rule failed) and `trainable_ref_train`. |
| `epic-kitchens/questions/train_2026-10-18.json` + `_split.json` | the 68,465 trainable questions (64,439 train / 4,026 val, on 27 validation videos) |
| `epic-kitchens/questions/train_2026-10-18_reftrain.json` + `_split.json` | the 67,070 of them whose every reference image has 3D (for `--ref_pos train`) |
| `epic-kitchens/hand_masks/hand_masks_2026-10-18.tar` | box + palm hand masks, 599 videos each (unpacks to `epic-kitchens/hand_masks/{box,palm}/`). They supersede the loose 572-video `hand_masks/{box,palm}/` files, whose rows are identical. |
| `epic-kitchens/meta/fps_table_2026-10-18.tar` | `Videos/<P>/{frames,durations}.txt` for the 599 videos: the voxel builder's fps table |
| `epic-kitchens/reference_frames/reftok-4b_2026-10-18.tar` | 24,727 reference-image token files (144 x 2560, or 192 x 2560 for the two 4:3 videos) |
| `epic-kitchens/reference_frames/refgeo-4b_2026-10-18.tar` | 23,015 exact-frame 3D files, one per reference image: per-token xyz and depth, camera pose, source. They come from the frame's EPIC-Fields pose, or a pose interpolated within 0.5 s, plus DA3 depth; otherwise from the nearest posed cached frame within 0.5 s. |
| `epic-kitchens/reference_frames/ref512_jpg_2026-10-18.tar` | the 512 px reference images the tokens were made from (needed only to re-bake them) |
| `epic-kitchens/v3_MANIFEST.tsv` | bytes, md5 and sha256 of every v3 file above except the tokens |

**Renamed on 2026-10-19 so every v3 file carries one date.** The question files were named after the day the questions
were frozen: `questions_2026-10-12.tar`, `LIST_2026-10-12.{csv,md}`, `labels_2026-10-12.jsonl` and `train_1012[_reftrain][_split].json`.
Only the names changed. Every loose file is byte-identical, and the tar holds the same 65 files under the folder `2026-10-18/`
instead of `2026-10-12/`. The old files remain in this repo's history.

## HD-EPIC reference geometry (added 2026-10-20)

| path | what |
|---|---|
| `hd-epic/reference_frames/hdepic_refgeo-4b_2026-10-18.tar` | 2,847 files (22 MB), one per reference image of the HD-EPIC VQA questions (2,650 questions). Each holds the camera pose (Aria SLAM world), the depth of each token and each token's MEAN 3D point (12 x 12 tokens of a 384 px, 95-degree rectified frame). md5 `65381813477968f5deef7aebb04e88e1` |

* **Who needs it:** only someone TESTING on HD-EPIC a model trained with `ref_pos=train`. Unpack it into
  `<code>/results/cache/hdepic/` (it creates `refgeo-4b/`).
* **One recording is empty:** the 51 references of P03-20240217-131219 hold NaN, because its released SLAM poses stop
  at 22.8 of 54.6 minutes. None of its questions is in a scored set.
* **Where it comes from:** HD-EPIC (Perrett et al., CVPR 2025). Cite it and follow its terms.
* **The rest of the HD-EPIC test data is not public:** no HD-EPIC images, videos or tokens are in this share.

## Earlier versions (kept, not used by v3)

| path | what |
|---|---|
| `epic-kitchens/frames/<video>.tar` | rectified 992 px frames of the 2026-10-06 version, `<video>/<frame:06d>.jpg`, 572 videos |
| `epic-kitchens/questions/questions.tar` | the 2026-10-06 question set (`all.json`, `covered.json`, `split_videos.json`) |
| `epic-kitchens/train/train.tar` | the v1 training lists (`text_only/epic_v1_*`, `reference_frames/epic_v1_refzs_*`) |
| `epic-kitchens/reference_frames/reference_frames.tar` | the v1 reference images |
| `epic-kitchens/raw/*.tar` | EPIC-Fields poses, Intermediate-Data (per-frame poses), VISOR and the EPIC annotations |
| `<category>/outdated-2026-09-24/` | the 2026-09-24 version (old layout: its members start with `task_runtime/`) |

`MD5SUMS.txt` lists every tar and loose v3 file, and `SHA256SUMS_tokens.txt` lists every token file.
`bash download.sh <DATA>` checks both and unpacks the tars that belong under the data root.