ByteDepth: Multi-Camera Depth Estimation Dataset

ByteDepth is a multi-camera depth estimation dataset containing synchronized depth, color, and auxiliary data. It comprises 39 recording sessions captured from various 3D cameras in indoor scenarios. The dataset was created by ericonaldo and last updated on July 12, 2025.

Use Cases

• Training multi-camera depth estimation models based on synchronized depth and color data.
• Benchmarking depth prediction algorithms based on the provided indoor scenarios.
• Developing sensor fusion techniques based on the auxiliary data captured alongside depth and color streams.
• Evaluating the generalization of depth models across different camera types mentioned in the description.

Strengths

• Contains 39 distinct recording sessions, providing multiple data capture scenarios.
• Includes synchronized data streams for depth, color, and auxiliary sensor inputs.
• Specifically designed for multi-camera setups, a key feature for certain computer vision tasks.

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 dataset size are unknown, which may limit suitability assessment.

Provenance

Source

huggingface

Collection Method

Captured from various 3D cameras in indoor scenarios.

Freshness

Last updated 2025-07-12 11:49:58; freshness should be verified.