Rekadaily 10k Egocentric Household Manipulation Data

RekaDaily-10k: Collecting 10,000+ Hours of Egocentric Household Manipulation Data

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Aug 6, 2026

RekaDaily-10k: Collecting 10,000+ Hours of Egocentric Household Manipulation Data

RekaDaily-10k: Collecting 10,000+ Hours of Egocentric Household Manipulation Data

To understand and simulate the physical world, omni world models and vision-language-action models need more than text. They need high-quality visual data with descriptions of what is happening, recorded directly in the chaotic environments where real behavior occurs.

Search for cooking videos and you get an enormous library of edited, staged, tripod-mounted footage cut to keep the interesting parts. What a machine needs in order to learn a physical task is the opposite: one continuous first-person view of somebody actually doing it, at the speed they actually do it, in the mess they actually live in. Nobody uploads that, because nobody would watch it. That footage has to be commissioned. Teleoperated data is precise but slow to produce, and it tends to inherit the tidiness of the space it was recorded in. Synthetic scenes scale but smooth over the clutter of real homes. Real first-person recordings sit in between, and the reason there are not more of them is that somebody has to pay people to make them. Introducing RekaDaily-10k To meet our own requirements for scale and quality, and to satisfy the needs of the broader industrial community, we built Claru , Reka’s foundational data engine, which sources egocentric video through a global network of paid collectors. Today we are releasing RekaDaily-10k: unscripted, first-person recordings of everyday household life, captured across homes by paid collectors recording their own routines, with a significant share in 4K. We are contributing this dataset to the research community as part of our open ecosystem initiative, under Apache 2.0, and the raw tier is available now on Hugging Face, with the full 10,312 hours live by early next week. The dataset ships in two tiers: Raw tier. Unfiltered, raw footage, allowing teams to implement their own clipping, filtering, and annotation workflows. It has 10,312 hours.

Processed and captioned tier. Footage that has been through our processing pipeline , cut into shorter clips and captioned, for teams that want language supervision out of the box.

The Apache 2.0 licence covers commercial use and redistribution. Each clip ships as video with a text caption. The same recordings, released twice — pick where you want to start

10,000 HOURS AS RECORDED

Unscripted first-person household sessions from paid collectors

RAW TIER

The footage as collected

hours

as recorded

segments

full sessions

captions

none

best for

teams with their own pipeline

PROCESSED & CAPTIONED

Through the pipeline

hours

over 10,000+

segments

short clips

captions

one per clip

best for

language supervision out of the box

The release is Apache 2.0 and ungated, covering commercial use and redistribution. Roughly 1,670 hours are native 4K.

The Egocentric Landscape The egocentric ecosystem has grown quickly, and this release is meant to add to it with more videos showing egocentric activities. Ego4D established the modality and remains the reference corpus for daily life. Egocentric-10K and the larger releases that followed it showed how far first-person data can scale, and they cover industrial work in real production environments. EPIC-KITCHENS is still the gold-standard of ego-centric benchmarks of human activities. What RekaDaily-10k adds: Unscripted household activity recorded in real homes with detailed descriptions. Roughly 1,670 hours are in native 4K, which is a higher resolution than most large egocentric corpora carriers. Together, this makes it an ideal complement for teams building domestic AI where language supervision matters. Where The Footage Comes From Claru is a paid collection network of more than 100,000 people recording the physical world. Collectors join a project, pass a qualification assessment, then record, submit, and get paid per accepted hour. The work spans domestic life, commercial environments and skilled trades across several regions. This release draws on the household portion of that network, recorded by a subset of those collectors on phones in head mounts. Environment Diversity Because every collector records in their own home, the number of distinct environments rises with the number of people who contribute rather than with the number of hours recorded. Different kitchens, appliance models, cabinet layouts, floor plans, lighting conditions and degrees of clutter. Different outlets and switch plates, different packaging on the shelves, different signage languages, different weather through the windows. That kind of variation is difficult to produce any other way. Authentic and Unscripted The footage is unscripted, capturing the dirt and noise of the real world, and thus making the dataset valuable. Collectors record real activity instead of performing a task list, so sessions run long, hands leave frame, tasks get abandoned and resumed later, and people walk in and interrupt. That is roughly what a deployment environment looks like, and it is the part that is hard to arrange deliberately. Everyday Household Routines What people recorded is mostly household work and the routine around it. Laundry from the pile to the folded stack. Kitchen cleanup, dishes, unloading groceries, wiping surfaces. Reorganising rooms, closets and drawers. Sweeping, taking out the trash, watering plants, clearing a table, unboxing something new, changing a bulb or a battery. The short fiddly two-handed jobs are here precisely because no one would commission a teleop session for them, and they are still on everybody’s actual list. Consent and Privacy Paid Collector Consent This is footage recorded inside people’s homes, and publishing it openly raises the stakes on how it was obtained. Collectors are paid contractors who opt in, and every session is recorded with the wearer’s knowledge and agreement. Bystanders The wearer is not the only person a home camera sees, so bystanders are handled separately. Collectors are instructed to record only with the agreement of other adults present and to keep others out of frame where that is not possible, and footage that shows identifiable non-participants is flagged for review before it can be released. PII Screening...