PseudoKitchens: Synthetic Photorealistic Kitchen Renders with Object Annotations

PseudoKitchens is a synthetic dataset of photorealistic 3D kitchen renders with ground-truth concept annotations. It was created by author yoda-chicken and last updated on 2026-05-20. The dataset is designed for tasks such as recipe classification and spatial concept localisation.

Use Cases

• Recipe classification based on the presence of ingredients in kitchen scenes.
• Spatial concept localisation based on annotations describing ingredient locations.
• Training and evaluating computer vision models on photorealistic synthetic data.
• Benchmarking object detection algorithms in constrained, domain-specific environments.

Strengths

• Contains photorealistic 3D renders, suggesting high visual fidelity.
• Includes ground-truth concept annotations for objects, providing structured labels.
• Designed for specific, advanced tasks like spatial concept localisation.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and license are unknown, which may limit suitability assessment.

Provenance

Source

huggingface user yoda-chicken

Collection Method

Synthetically generated 3D renders.

Freshness

Last updated 2026-05-20 17:04:53; freshness should be verified.