ByteCameraDepth: Multi-Camera Depth Estimation Data for Indoor Scenarios

ByteCameraDepth is a multi-camera depth estimation dataset containing synchronized depth, color, and auxiliary data. It was created by ByteDance-Seed and last updated on Hugging Face on 2025-09 06. The dataset is intended for developing and evaluating depth estimation algorithms in various indoor scenarios.

Use Cases

• Benchmarking depth estimation models based on synchronized multi-camera data.
• Developing sensor fusion algorithms based on combined depth and color streams.
• Training models for 3D scene understanding in indoor environments based on the described scenarios.

Strengths

• Contains synchronized data from multiple cameras, providing aligned depth and color information.
• Specifically captured for various indoor scenarios, offering a focused environment for testing.

Limitations

• Row count, file formats, and column-level documentation are unknown, limiting suitability assessment.
• The dataset description is incomplete; full details require visiting the external project page.

Provenance

Source

ByteDance-Seed

Collection Method

Captured from various 3D cameras.

Time Range

null

Freshness

Last updated 2025-09-06 02:38:22.

Geography

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