Egocentric Car Washing and Vehicle Detailing Video Data

Egocentric car washing and detailing video data is real-world, first-person video of a person caring for a vehicle: washing and rinsing the body, drying and buffing it, polishing the paint, and vacuuming and wiping the interior. It is recorded from the operator viewpoint, with depth, 3D hand pose, contact events and frame-accurate action segments aligned on one hardware clock.

Vehicle care is long-horizon surface work, not a single grasp. A person covers a body panel by panel, changes tools between steps and keeps checking the result. The automotive page covers torque, fluid and diagnostic work, the tire page covers wheel machine work and the wiping page covers surface cleaning in general. This page centres on washing and detailing the vehicle itself.

The site states car washing and detailing in its task catalog. An environment called Car Wash & Detailing lists eight rows covering exterior washing, claying, drying and buffing, polishing, interior vacuuming and wheel and tire dressing. Two more rows sit in the Auto Service Center & Tire Shop environment: one washing and drying exteriors and one dressing wheels and tires.

Every row uses the same capture mode, a head-mounted phone or a multiview rig. Skill ratings run from Easy to Medium. Nine rows are Active collection and the service-environment dressing row is Ready to deploy. A custom spec is scoped from that vocabulary, with the catalog rows as a starting point rather than a fixed menu.

Four rows describe washing: a professional car wash using commercial equipment and chemicals, a wash and dry with a foam cannon and microfiber towels, a wash, clay and dry using wash mitts and a clay bar, and a wash, rinse, dry and polish with foam sprayers, mitts, towels and a polisher. The professional wash is rated Easy, and the clay and polish rows are Medium.

Drying and buffing is its own Easy row, and polishing is a Medium row that applies, buffs and inspects compound with a dual-action polisher and microfiber cloths. Action segments mark the boundaries between washing, drying, applying and buffing, which is where a policy has to sequence correctly.

The site gives no vehicle type, panel count, towel type, compound, polisher setting or gloss measurement. Those are agreed in the written spec, and no chemical or product is named here.

Two Easy rows cover the interior: Car Interior Vacuuming, described as vacuuming and cleaning vehicle interiors, seats, mats and trim, and a row that vacuums, wipes and conditions interiors with a shop vacuum and detailing brushes. A multiview rig adds a second angle when the cabin blocks the first-person view. Vacuuming rows for hotel rooms or offices are not counted, because they do not name a vehicle.

Wheel and tire dressing appears twice, both Easy: Car Wheel & Tire Dressing in the car wash environment, which is Active collection, and Wheel & Tire Dressing in the auto service environment, which is Ready to deploy. Heavier wheel work such as dismounting and balancing sits on the tire and wheel service page.

The catalog places the car wash rows in its Car Wash & Detailing environment, with car wash bays, a detailing shop and polishing stations as examples. Row descriptions add a car wash facility with wash bays, a drying area and a polishing station, and a detailing shop with detailing supplies.

Ready to deploy means contributors and site access are set up and capture starts once a spec is signed. Active collection means recording is running now, so a spec can join an existing capture stream. The site names no facility, brand or vehicle, and does not state capture at a customer own facility; environment, access and schedule are agreed in the spec.

A head-mounted phone records the first-person view of real work on site, and a multiview rig adds synchronized third-person angles when the spec asks for them. A wrist-mounted camera is available alongside the head camera for close-range detail.

The site does not state a camera count, resolution, frame rate or protection from water and spray for car washing, so none is claimed and all are worth raising in the spec. It does state that infrared depth is hostile on painted and oily automotive surfaces, so those episodes carry a depth-quality flag instead of being interpolated. Behaviour on wet or glossy paint is not stated.

Each episode follows the Firsthand episode schema: ten streams synced under 2 ms, with head and wrist RGB, depth, 3D hand pose with per-joint visibility, contact and grasp events, and frame-accurate action segments. For vehicle care, hand pose tracks the wipe, rinse and buff, contact events mark when fingers meet a mitt, towel or tool, and action segments mark each step.

Object labels use the terms your spec sets. Vehicle makes or models, number of sites or vehicles, chemical or product names, water or pressure settings, device models, throughput, force or tactile data and a task-completion label are Not stated. They are defined in the spec if your policy needs them, and no safety or compliance claim is made.

Delivery formats are RLDS, LeRobot and WebDataset, plus HDF5, zarr and Rerun .rrd. The format table below sets each against what its official documentation states. Car washing episodes use the same schema as every other Firsthand collection, so a loader that reads another Firsthand dataset reads this one without changes.

Every batch is validated against signed accept criteria before it ships, with a reject log, and delivery is rolling, per validated batch.

Every episode links to a signed contributor release through a documented consent chain, and the consent record is part of the delivery. Faces, plates and screens are detected and irreversibly blurred at ingest, and a reviewer confirms the result before anything ships. The anonymization record is delivered with the data.

The site does not state a separate rule for other vehicle text such as badges or stickers, so this page does not claim it is blurred. Raise it in the spec if it matters.

Where coverage is already deep, the first validated batch lands in a median of 48 hours from signed spec. Thin environments typically take three to four weeks, because vetting operators there is the bottleneck, and we quote that up front. The car wash rows are currently Active collection or Ready to deploy.

On-demand top-ups run against the same spec and accept criteria after each training run. The site does not state a batch size or later-batch turnaround, so those are quoted against your spec.

You describe the vehicles, stations and sequence your policy needs. We turn that into a written spec covering tasks, environments, capture tier, annotation depth and accept criteria, then quote reach, timeline and price before any capture begins.

A Spec Pilot, a small and fast first batch, can prove the spec and accept criteria before you scale. Billing is per validated hour, a reject log ships with every batch, rejected items are recaptured at our cost, and every collection ships under a perpetual, buyer-owned commercial license.