PolypSense3D is a multi-source benchmark dataset designed specifically for depth-sensing polyp size measurement tasks, released in 2025 by Hangzhou Normal University in collaboration with the Technical University of Denmark, Hohai University, and other institutions. Related research papers include... PolypSense3D: A Multi-Source Benchmark Dataset for Depth-Aware Polyp Size Measurement in EndoscopyIt has been selected for NeurIPS 2025 and aims to provide high-quality training and evaluation resources for polyp detection, depth estimation, size measurement and simulation-to-real transfer research.

Data Scale and Composition

This dataset integrates three types of data: virtual simulation, physical phantoms, and real clinical scenarios.

• Virtual simulation data: Contains 32,000+ frames, providing synchronized RGB, dense depth, segmentation mask, and camera parameters, and covers 30 procedural polyp models (1.79–20.52 mm) for training and evaluation under high-precision, controlled conditions.

• Physical data: Contains 13 videos derived from a colonic phantom constructed and 3D printed based on real CT scans, with 13 solid polyps (4.00–14.89 mm) embedded, and with rigorously calibrated camera parameters for sim-to-real migration validation.
• Clinical data: derived from standard clinical colonoscopy examinations, including stable frozen frames, providing manual and model-assisted segmentation, dimension annotation based on calibrated biopsy forceps, and sparse depth annotation for model evaluation under real-world conditions.