Ifirsthand

A ready-made, commercially licensed egocentric multimodal dataset of live retail shelf operations - facing and front-stocking to a planogram, case-cut and shelf-load, price and label swaps, chilled-case rotation by date code, and hanger and fixture resets - captured on operating sales floors with customers present across ten hardware-synchronized streams: 4K60 global-shutter head camera, two 1080p60 wrist cameras, active-stereo depth in metric millimetres, 200 Hz 6-DoF IMU, 3D 21-keypoint hand pose with grasp and release contact events, body pose, instance masks and frame-accurate per-skill action segments, all on one clock with under 2 ms sync

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Coverage

Universe, instruments and categories.

Industry: Application SoftwareFood Retail
Instruments: equities
Categories: AlternativeGeospatial
Regions: US
Sample tickers: SERVWMTKRACICOSTPGCLMDLZ

Dataset card

Type: not stated
Format: Multimodal time-series and video (H.265 video with lossless keyframes, metric depth with per-frame confidence maps, IMU, 3D pose, instance masks, per-frame action segments) packaged in machine-learning-native formats - RLDS, LeRobot and WebDataset, plus HDF5, zarr and .rrd
Volume: 890 validated hours across 6,210 episodes from 96 participants at 31 capture sites, with ten synchronized streams per episode - head video at 3840x2160 at 60 frames per second, two wrist streams at 1920x1080 at 60 frames per second, depth at 848x480 at 30 frames per second and 200 Hz inertial measurement, so on the order of 190 million head-camera frames plus comparable multi-stream volume in the terabyte range; median episode 78 seconds, or 41 seconds for chilled-case work
Users: N/A - a business-to-business dataset and collection service sold through direct licensing, with no consumer or self-serve accounts; the vendor's own published capture population is 96 consented participants
History: not stated
Update frequency: not stated
Growth: Active - the retail shelf-stocking set is labelled as shipping, condition-cell fill rates are reported as current coverage, and failure-case coverage at 14 percent is described as the thinnest in the wider catalog, indicating an actively expanding collection program
Launched: ~2024-2026 (inferred: the embodied-AI dataset arm is a recent venture built on top of CloudPano, an established spatial-data software company, and the embodied-AI dataset market it targets emerged in this window; no launch date is printed on the page)
Delivery: not stated
Entity mapping: not stated
Sample: not stated
Point-in-time: not stated
Licence: not stated

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