SCARED-C: Corrected Camera Poses for Endoscopic Depth Estimation
For researchers in endoscopic depth estimation, this provides a significantly larger and more reliable benchmark dataset.
The SCARED dataset for endoscopic depth estimation had pose errors limiting reliable data to 35 keyframes. SCARED-C corrects poses using COLMAP and scale recovery, expanding reliable RGB-D pairs to 17,135.
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.