# Doppelgangers++: Improved Visual Disambiguation with Geometric 3D Features

arXiv: https://arxiv.org/abs/2412.05826 · HTML: https://mlsanity.com/paper/2412.05826/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 35 references that are in the map.
- First posted on arXiv 8 Dec 2024.

## Builds on (most cited first, 14 of 14)

- [DUSt3R: Geometric 3D Vision Made Easy](https://mlsanity.com/paper/2312.14132/) (2023)
- [SuperGlue: Learning Feature Matching with Graph Neural Networks](https://mlsanity.com/paper/1911.11763/) (2019)
- [SuperPoint: Self-Supervised Interest Point Detection and Description](https://mlsanity.com/paper/1712.07629/) (2017)
- [LoFTR: Detector-Free Local Feature Matching with Transformers](https://mlsanity.com/paper/2104.00680/) (2021)
- [Grounding Image Matching in 3D with MASt3R](https://mlsanity.com/paper/2406.09756/) (2024)
- [D2-Net: A Trainable CNN for Joint Detection and Description of Local Features](https://mlsanity.com/paper/1905.03561/) (2019)
- [LIFT: Learned Invariant Feature Transform](https://mlsanity.com/paper/1603.09114/) (2016)
- [Visual Geometry Grounded Deep Structure From Motion](https://mlsanity.com/paper/2312.04563/) (2023)
- [Neighbourhood Consensus Networks](https://mlsanity.com/paper/1810.10510/) (2018)
- [MASt3R-SfM: a Fully-Integrated Solution for Unconstrained Structure-from-Motion](https://mlsanity.com/paper/2409.19152/) (2024)
- [Scene Coordinate Reconstruction: Posing of Image Collections via Incremental Learning of a Relocalizer](https://mlsanity.com/paper/2404.14351/) (2024)
- [MegaScenes: Scene-Level View Synthesis at Scale](https://mlsanity.com/paper/2406.11819/) (2024)
- [Doppelgangers: Learning to Disambiguate Images of Similar Structures](https://mlsanity.com/paper/2309.02420/) (2023)
- [Fine-grained Activities of People Worldwide](https://mlsanity.com/paper/2207.05182/) (2022)

## Built on by (most cited first, 20 of 20)

- [LoMa: Local Feature Matching Revisited](https://mlsanity.com/paper/2604.04931/) (2026)
- [Global Structure-from-Motion Meets Feedforward Reconstruction](https://mlsanity.com/paper/2605.26103/) (2026)
- [GECO: Geometrically Consistent Embedding with Lightspeed Inference](https://mlsanity.com/paper/2508.00746/) (2025)
- [Emergent Extreme-View Geometry in 3D Foundation Models](https://mlsanity.com/paper/2511.22686/) (2025)
- [Long-tail Internet photo reconstruction](https://mlsanity.com/paper/2604.22714/) (2026)
- [Unconstrained Large-scale 3D Reconstruction and Rendering across Altitudes](https://mlsanity.com/paper/2505.00734/) (2025)
- [VidMap: Exploiting Temporal Structure for Video-Based Structure-from-Motion](https://mlsanity.com/paper/2607.27194/) (2026)
- [Global-Aware Edge Prioritization for Pose Graph Initialization](https://mlsanity.com/paper/2602.21963/) (2026)
- [Wrivinder: Towards Spatial Intelligence for Geo-locating Ground Images onto Satellite Imagery](https://mlsanity.com/paper/2602.14929/) (2026)
- [Privacy-Preserving Structureless Visual Localization via Image Obfuscation](https://mlsanity.com/paper/2604.12068/) (2026)
- [ArchSym: Detecting 3D-Grounded Architectural Symmetries in the Wild](https://mlsanity.com/paper/2604.22202/) (2026)
- [Can These Views Be One Scene? Evaluating Multiview 3D Consistency when 3D Foundation Models Hallucinate](https://mlsanity.com/paper/2605.18754/) (2026)
- [Honey, I Shrunk the Arc de Triomphe!](https://mlsanity.com/paper/2606.02379/) (2026)
- [DGSfM: Depth-Guided Scale-Aware Global Structure-from-Motion](https://mlsanity.com/paper/2607.09507/) (2026)
- [Robust Global Structure-from-Motion via View Graph Pruning](https://mlsanity.com/paper/2608.22054/) (2026)
- [Ground-to-Satellite Localization in Unconstrained Image Collections for 3D Scene Reconstruction](https://mlsanity.com/paper/2608.29211/) (2026)
- [XDG: Accelerated Visual Disambiguation](https://mlsanity.com/paper/2608.29733/) (2026)
- [HiSfM: Disambiguating Structure-from-Motion via Scaffold-Anchored Hierarchical Reconstruction](https://mlsanity.com/paper/2609.04718/) (2026)
- [MVDG: Efficient Multi-view 3D Disambiguation on Unconstrained Real-World Images](https://mlsanity.com/paper/2610.01098/) (2026)
- [Graph3R: Unifying View Graph Initialization with Feed-Forward Reconstruction](https://mlsanity.com/paper/2610.16272/) (2026)

## Abstract (arXiv)

Accurate 3D reconstruction is frequently hindered by visual aliasing, where visually similar but distinct surfaces (aka, doppelgangers), are incorrectly matched. These spurious matches distort the structure-from-motion (SfM) process, leading to misplaced model elements and reduced accuracy. Prior efforts addressed this with CNN classifiers trained on curated datasets, but these approaches struggle to generalize across diverse real-world scenes and can require extensive parameter tuning. In this work, we present Doppelgangers++, a method to enhance doppelganger detection and improve 3D reconstruction accuracy. Our contributions include a diversified training dataset that incorporates geo-tagged images from everyday scenes to expand robustness beyond landmark-based datasets. We further propose a Transformer-based classifier that leverages 3D-aware features from the MASt3R model, achieving superior precision and recall across both in-domain and out-of-domain tests. Doppelgangers++ integrates seamlessly into standard SfM and MASt3R-SfM pipelines, offering efficiency and adaptability across varied scenes. To evaluate SfM accuracy, we introduce an automated, geotag-based method for validating reconstructed models, eliminating the need for manual inspection. Through extensive experiments, we demonstrate that Doppelgangers++ significantly enhances pairwise visual disambiguation and improves 3D reconstruction quality in complex and diverse scenarios.