Evaluating Zero-Shot Monocular Depth Estimation Models for Tactile Rendering of Paintings
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Access to pictorial art remains a significant challenge for visually impaired individuals, as 2D paintings require transformation into tactile 2.5D/3D models. While deep learning offers promising tools for monocular depth estimation (MDE), applying state-of-the-art zero-shot models to artworks presents unique difficulties due to artistic conventions (perspective, lighting, texture) and the lack of ground truth, especially concerning details crucial for tactile perception. This paper addresses this gap by qualitatively evaluating a wide range of SOTA zero-shot MDE models - including DepthAnything (v1/v2), Marigold, Metric3D v2, ZoeDepth, UniDepth (v1/v2/v2_old), GeoWizard (v1/v2), and Depth-Pro - on their ability to generate depth maps suitable for tactile rendering from two 20th-century Italian paintings with distinct styles and input qualities. The assessment, based on criteria like detail preservation, contour definition, spatial coherence, and artifact absence, reveals that while zero-shot models can interpret basic spatial structures, performance varies considerably. Models such as DepthAnything v2 and GeoWizard v2 demonstrated superior capabilities in preserving key features for tactile fruition, emerging as promising candidates. However, no model produced a directly usable output, highlighting persistent challenges in handling artistic styles and pictorial textures. This study provides the first systematic comparison in this niche application, offering practical insights for cultural institutions aiming to leverage AI for accessibility. It concludes that current zero-shot models, while valuable starting points requiring validation and refinement, show significant potential but also underscore the need for further research in areas like targeted post-processing, art-specific metrics, and user-centered validation to make cultural heritage truly accessible to all.
Description
@inproceedings{10.2312:dh.20253048,
booktitle = {Digital Heritage},
editor = {Campana, Stefano and Ferdani, Daniele and Graf, Holger and Guidi, Gabriele and Hegarty, Zackary and Pescarin, Sofia and Remondino, Fabio},
title = {{Evaluating Zero-Shot Monocular Depth Estimation Models for Tactile Rendering of Paintings}},
author = {Magherini, Roberto and Servi, Michaela and Buonamici, Francesco and Furferi, Rocco},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-277-6},
DOI = {10.2312/dh.20253048}
}