# SCARED-C: Corrected Camera Poses for Endoscopic Depth Estimation

arXiv: https://arxiv.org/abs/2605.16628 · HTML: https://mlsanity.com/paper/2605.16628/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 12 references that are in the map.
- First posted on arXiv 15 May 2026.

## Builds on (most cited first, 9 of 9)

- [FoundationStereo: Zero-Shot Stereo Matching](https://mlsanity.com/paper/2501.09898/) (2025)
- [Stereo Correspondence and Reconstruction of Endoscopic Data Challenge](https://mlsanity.com/paper/2101.01133/) (2021)
- [Colonoscopy 3D Video Dataset with Paired Depth from 2D-3D Registration](https://mlsanity.com/paper/2206.08903/) (2022)
- [Fast-FoundationStereo: Real-Time Zero-Shot Stereo Matching](https://mlsanity.com/paper/2512.11130/) (2025)
- [C3VDv2 -- Colonoscopy 3D video dataset with enhanced realism](https://mlsanity.com/paper/2506.24074/) (2025)
- [Depth Anything in Medical Images: A Comparative Study](https://mlsanity.com/paper/2401.16600/) (2024)
- [From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction](https://mlsanity.com/paper/2503.16263/) (2025)
- [SimuScope: Realistic Endoscopic Synthetic Dataset Generation through Surgical Simulation and Diffusion Models](https://mlsanity.com/paper/2412.02332/) (2024)
- [RealSynCol: a high-fidelity synthetic colon dataset for 3D reconstruction applications](https://mlsanity.com/paper/2602.08397/) (2026)

## Built on by (most cited first, 1 of 1)

- [DART: Depth-as-Target Pretraining for Surgical Vision Foundation Models](https://mlsanity.com/paper/2609.04555/) (2026)

## 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.