Egocentric Bathroom Cleaning Video Data

It is first-person video of a person cleaning a bathroom or restroom, recorded from the contributor’s own point of view with synchronized sensor streams alongside. The frame shows what the person sees: the fixture, the brush or cloth in one hand, the other hand steadying or reaching and the surface being cleaned.

The key word is cleaning as a sequence: scrubbing, spraying, wiping, mopping and restocking in an order. In the catalog that covers guest bathrooms in hotels and restrooms in commercial cleaning, from a short wipe-down to a deep clean of tiles, grout, fixtures and drains.

Firsthand captures humans, not robots. Episodes carry human hand pose and human action labels. The site states no robot actions, robot joint data or teleoperation data for this task family, so using the episodes for a specific robot still needs your own retargeting step.

The task catalog names seven rows that are explicitly about cleaning a bathroom or restroom. Three sit in Hotel & Lodging: "Bathroom cleaning", "Clean and restock guest bathrooms using disinfectant and amenity kits" and "Hotel Bathroom Deep Clean". All three are Ready to deploy. The first two are Easy skill level and the deep clean is Medium.

Four sit in Commercial Cleaning & Janitorial: "Clean and disinfect restrooms using disinfectant sprayers and mops", "Restroom cleaning", "Event Restroom Sanitation" and "Restroom Restock & Disinfection". All are Easy skill level. Two are Active collection and two are Ready to deploy. Every row lists a head-mounted phone or multiview rig.

Ready to deploy and Active collection are different statuses and the catalog does not define either further, so ask which applies to your row. The second table lists neighbouring rows, such as housekeeping, that are not bathroom cleaning rows themselves.

The catalog ties bathroom cleaning to two environments: Hotel & Lodging, with examples such as guest room servicing, resort housekeeping and bathroom cleaning, and Commercial Cleaning & Janitorial, with examples such as an office building, shopping mall, airport or industrial facility. The site does not state capture at a customer’s own facility.

Fixture types, surface materials, cleaning products and room layout are not stated for any row, so they are agreed in the spec. The capture setup table lists the hardware as the site states it.

An episode is one contributor performing one task from the skill spec, recorded with ten hardware-synchronized streams that line up within 2 ms. The site documents a canonical episode schema, and every delivery format is a view of it. The fields that matter most for cleaning are listed in the episode fields table.

Hand pose is stored as 21 joints per hand in metres in the head frame, with a visibility flag for each joint. Contact events record when a hand meets an object. The site does not say whether a fixture, a brush or a spray bottle counts as the object, so settle what a contact event means for your task in the spec.

Action segments carry a start, an end, a verb and a noun from a taxonomy the site states as 97 verbs and 512 nouns, human-reviewed. For bathroom cleaning, a segment can be one step as written in the spec. Every episode links to its contributor’s signed release by a consent artefact ID, and each batch ships with a data card.

The unit of labeling is the action segment, which is why the way you write the spec decides how useful the data is. A spec that says "clean the bathroom" gives you one long segment. A spec that names the steps and the fixtures gives you a sequence you can train on and slice by step.

Every episode is machine-checked, then reviewed by a human against its skill spec, and rejected episodes are recaptured at our cost. The site states no label for fixture type, surface material, cleanliness or task success, and no force or tactile reading, so ask for any such label at the start.

Only what the site already states applies. Every contributor signs a written release, and each episode links to it. Faces, plates and screens are detected and blurred irreversibly, a human reviewer confirms that no un-consented person is identifiable, and footage that cannot be de-identified is discarded rather than shipped.

For household capture the site adds a stricter rule: bathroom capture excludes any episode with a person in frame other than the consenting operator. The site does not say whether the same rule is applied to hotel guest bathrooms or commercial restrooms, so settle it in the spec before capture. This is not legal advice, and the executed agreement controls.

Data is delivered in RLDS, LeRobot, WebDataset, HDF5, zarr or Rerun .rrd, or as raw streams with metadata, with the episode schema as the canonical layout. QA runs once, against the canonical episode, before any format is cut. The formats table sets the site’s delivery next to each maintainer’s own documentation, linked under Sources.

The license is perpetual, irrevocable and worldwide, buyer-owned and non-exclusive by default, with exclusivity available as a separate term and the executed order form governing.

The site states one published timeline: from a signed spec to a first validated batch, a median of 48 hours where coverage is already deep, and typically three to four weeks where it is thin because operators have to be staffed. The site does not say which applies to the bathroom rows and promises nothing faster, so ask when you request the quote.

Collection is on demand, so a focused brief, such as one named restroom clean from first spray to last restock, is a normal starting point.

Start with the free sample pack to check the loader and label quality, then move to a Spec Pilot: a small, fast first batch against the written spec that proves the fill rate and reject rate on your conditions before you scale, so a gap in the spec shows up on a handful of episodes.

A good bathroom brief names the room type, the fixtures and the order of steps, how each step starts and ends, what counts as a reject and the privacy rule for the room. The site’s skill-spec guide walks through that structure. Then request a custom dataset and we will quote reach, timeline and price against the spec.