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ETH3D Multi-View Stereo Benchmark Dataset (Relative Depth).

ETH3D is a comprehensive multi-view stereo and SLAM benchmark dataset designed for evaluating 3D reconstruction algorithms. Developed by the Computer Vision and Geometry Group at ETH Zurich, it features a wide variety of indoor and outdoor scenes, captured using both high-resolution DSLR cameras and synchronized multi-camera video systems. Ground truth geometry is obtained using high-precision laser scans. The benchmark consists of multiple challenges: high-res multi-view stereo with 13 training and 12 test scenes using DSLR images, low-res many-view stereo on video data with 5 training and 5 test sequences, and low-res two-view stereo with 27 training and 20 test frames. ETH3D is intended to advance research in 3D reconstruction by providing accurate ground truth and challenging scenarios, including mobile and hand-held camera use cases. The dataset offers rich visualizations and an online evaluation server.

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What a submission needs
  • 01A public checkpoint or API endpoint
  • 02A reproduction script with frozen commit + seed
  • 03Declared evaluation environment (Python, deps)
  • 04One row per metric declared by this dataset
  • 05A contact so we can follow up on discrepancies