Many Eyes, One World: Feed-Forward 3D Reconstruction from Mixed Cameras

arXiv:2609.35658 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Terminology

• Benchmark — 27× in this paper · explained in 2 episodes
• AUC — 26× in this paper · explained in 2 episodes
• Calibration — 23× in this paper · explained in 7 episodes
• Alignment — 12× in this paper · explained in 1 episode
• Adaptation — 9× in this paper · explained in 1 episode
• Accuracy — 6× in this paper · explained in 1 episode
• Foundation Model — 6× in this paper · explained in 3 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Foundation Models — 4× in this paper · explained in 7 episodes
• In European Conference on Computer Vision — 3× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• In International Conference on Learning Representations — 2× in this paper
• Benchmarking — 1× in this paper · explained in 3 episodes
• CVF International Conference on Computer Vision — 1× in this paper
• Digital Twin — 1× in this paper · explained in 5 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes

Sources

• Joint 2D-3D-Semantic Data for Indoor Scene Understanding
• Unified Panoramic Geometry Estimation via Multi-View Foundation Models
• MUSt3R: Multi-view Network for Stereo 3D Reconstruction
• Fisheye3R: Adapting Unified 3D Feed-Forward Foundation Models to Fisheye Lenses
• UniDAC: Universal Metric Depth Estimation for Any Camera
• Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens
• PanoVGGT: Feed-Forward 3D Reconstruction from Panoramic Imagery
• Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera
• CAM3R: Camera-Agnostic Model for 3D Reconstruction
• RIGOR: Rig-Informed Geometry for Omnidirectional Reconstruction
• Pow3R: Empowering Unconstrained 3D Reconstruction with Camera and Scene Priors
• Wid3R: Wide Field-of-View 3D Reconstruction via Camera Model Conditioning
• MapAnything: Universal Feed-Forward Metric 3D Reconstruction
• CalibAnyView: Beyond Single-View Camera Calibration in the Wild
• Rig3R: Rig-Aware Conditioning for Learned 3D Reconstruction
• Depth Any Panoramas: A Foundation Model for Panoramic Depth Estimation
• CM-EVS: Sparse Panoramic RGB-D-Pose Data for Complete Scene Coverage
• SimpleProc: Fully Procedural Synthetic Data from Simple Rules for Multi-View Stereo
• Holo360D: A Large-Scale Real-World Dataset with Continuous Trajectories for Advancing Panoramic 3D Reconstruction and Beyond
• RayTun3R: Online Camera Adaptation in 3D Foundation Models

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