SCARED-C: Corrected Camera Poses for Endoscopic Depth Estimation
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Abstract (arXiv)
The SCARED dataset is a widely used benchmark for endoscopic depth estimation, offering ground-truth 3D reconstructions captured with a structured light sensor. However, the depth maps for non-keyframe images rely on robot kinematics that introduce substantial pose errors, limiting the reliably labeled portion of the dataset to 35 keyframes. We present SCARED-C, a corrected version of the SCARED dataset that expands the number of reliable RGB-D pairs from 35 to 17,135. Our pipeline applies COLMAP, a Structure-from-Motion system, to re-estimate camera poses for all frames, followed by a scale recovery step that aligns the resulting reconstructions to metric space using the ground-truth keyframe depth maps. We validate the corrected poses through (1) stereo disparity evaluation and (2) monocular depth estimation experiments. The corrected dataset and code are publicly released to the community.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 9 of its 12 references that are in the map. First posted on arXiv 15 May 2026.
Builds on
9 of 12 references.
References · 9
- 2025FoundationStereo: Zero-Shot Stereo Matchingcited by 168
- 2021Stereo Correspondence and Reconstruction of Endoscopic Data Challengecited by 101
- 2022Colonoscopy 3D Video Dataset with Paired Depth from 2D-3D Registrationcited by 78
- 2025Fast-FoundationStereo: Real-Time Zero-Shot Stereo Matchingcited by 23
- 2025C3VDv2 -- Colonoscopy 3D video dataset with enhanced realismcited by 14
- 2024Depth Anything in Medical Images: A Comparative Studycited by 13
- 2025From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstructioncited by 10
- 2024SimuScope: Realistic Endoscopic Synthetic Dataset Generation through Surgical Simulation and Diffusion Modelscited by 8
- 2026RealSynCol: a high-fidelity synthetic colon dataset for 3D reconstruction applicationscited by 1
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Citing papers per year: 2026: 1.
1 paper.