Reflect3r: Single-View 3D Stereo Reconstruction Aided by Mirror Reflections

• URL: http://arxiv.org/abs/2509.20607v1
• Date: Wed, 24 Sep 2025 23:00:22 GMT
• Title: Reflect3r: Single-View 3D Stereo Reconstruction Aided by Mirror Reflections
• Authors: Jing Wu, Zirui Wang, Iro Laina, Victor Adrian Prisacariu,
• Abstract summary: Mirror reflections are common in everyday environments and can provide stereo information within a single capture.<n>We exploit this property by treating the reflection as an auxiliary view and designing a transformation that constructs a physically valid virtual camera.<n>This enables a multi-view stereo setup from a single image, simplifying the imaging process.
• Score: 55.248092751290834
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Mirror reflections are common in everyday environments and can provide stereo information within a single capture, as the real and reflected virtual views are visible simultaneously. We exploit this property by treating the reflection as an auxiliary view and designing a transformation that constructs a physically valid virtual camera, allowing direct pixel-domain generation of the virtual view while adhering to the real-world imaging process. This enables a multi-view stereo setup from a single image, simplifying the imaging process, making it compatible with powerful feed-forward reconstruction models for generalizable and robust 3D reconstruction. To further exploit the geometric symmetry introduced by mirrors, we propose a symmetric-aware loss to refine pose estimation. Our framework also naturally extends to dynamic scenes, where each frame contains a mirror reflection, enabling efficient per-frame geometry recovery. For quantitative evaluation, we provide a fully customizable synthetic dataset of 16 Blender scenes, each with ground-truth point clouds and camera poses. Extensive experiments on real-world data and synthetic data are conducted to illustrate the effectiveness of our method.

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