Building the largest reality-grade 3D dataset
We're building a dataset that redefines what’s possible in 3D content generation — ultra-realistic, relightable, and at massive scale. Already used by Meta Reality Labs, now available to the wider research and enterprise ecosystem.
A new standard for 3D datasets
Despite progress in generative Al, most training datasets remain limited while not being 3D native. Popular examples like Objaverse, Google Scanned Objects, and ShapeNet offer scale but lack realism, consistency, or usable metadata.
ALLSIDES closes this gap with reality-grade, relightable, 3D data suited for ML-applications. Depicting real objects scanned at industrial scale, our dataset doesn't approximate the physical world - it captures it.
Get a first glimpse of our dataset. Click here to download some examples of raw scans, straight from the scanner
The Digital Twin Catalog by Meta
We partnered with Meta to release the Digital Twin Catalog, the most photorealistic open-source 3D dataset to date. Our scanners powered the object capture pipeline behind the dataset.
Comparison Table
Existing Solutions | Our Solution | |
| QUALITY | Synthetic data or low-fidelity assets | High quality real-world objects: sub-mm geometric accuracy, HD pbr textures |
| LIGHT | Lighting is baked into textures | Relightable assets — enabling fully controllable rendering in any scene or lighting condition |
| GEOMETRY | Low poly with poor surface details and broken topology | Clean, watertight and optimized meshes, with high-fidelity surface |
| METADATA | Inconsistent metadata and no structured object info | Every object is tagged with structured metadata (category, size, geometry/texture quality, date, etc.) |
| DIVERSITY | Limited variety across object categories, textures, brands, functions... | Real consumer goods (food, footwear, accessories, kitchenware...) spanning different shapes, materials, manufacturers, and use cases |
At a glance
A digital archive of physical objects. Our vast dataset spans countless categories and materials, creating the most comprehensive 3D model repository for advancing computer vision, Al research, content creation and immersive digital experiences.
+ Multiple formats: GLB, USDZ, OBJ, and custom
+ Structured metadata per SKU (material, category, brand, dimensions
Want access to the dataset?
We’re actively onboarding select research and enterprise partners. Reach out to discuss licensing, collaboration, or use cases.