GeoMix achieves new state-of-the-art results in descriptor-free 2D-3D matching by adding directional embeddings, learnable global context nodes, and multi-detector training, cutting rotation and translation errors by up to 90% on standard benchmarks.
Reloc3R: Large-Scale Training of Relative Camera Pose Regression for Generalizable, Fast, and Accurate Visual Localization
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CasaMaestro predicts metric depth and poses from sparse multi-view panoramas to enable fast house-scale 3D reconstruction.
3DReflecNet is a 22 TB+ dataset of over 120,000 synthetic and 1,000 real objects with millions of multi-view frames for benchmarking 3D reconstruction on reflective, transparent, and low-texture surfaces.
FastForward represents scenes as collections of 3D-anchored image features and performs camera pose estimation via feed-forward correspondence prediction, achieving competitive accuracy with minimal mapping time.
VGGT-SLAM aligns VGGT submaps via SL(4) manifold optimization of 15-DoF homographies to enable consistent dense RGB SLAM on long uncalibrated monocular videos.
Simple image obfuscation enables privacy-preserving structureless visual localization with standard feature matchers and no pipeline changes, achieving state-of-the-art accuracy among privacy methods.
TTT3R derives a closed-form learning rate from memory-observation alignment confidence to boost length generalization in RNN-based 3D reconstruction by 2x in global pose estimation.
citing papers explorer
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GeoMix: Descriptor-Free Visual Localization via Global Context and Multi-Detector Training
GeoMix achieves new state-of-the-art results in descriptor-free 2D-3D matching by adding directional embeddings, learnable global context nodes, and multi-detector training, cutting rotation and translation errors by up to 90% on standard benchmarks.
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CasaMaestro: Multi-View Panoramas for House-Scale 3D Reconstruction
CasaMaestro predicts metric depth and poses from sparse multi-view panoramas to enable fast house-scale 3D reconstruction.
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3DReflecNet: A Large-Scale Dataset for 3D Reconstruction of Reflective, Transparent, and Low-Texture Objects
3DReflecNet is a 22 TB+ dataset of over 120,000 synthetic and 1,000 real objects with millions of multi-view frames for benchmarking 3D reconstruction on reflective, transparent, and low-texture surfaces.
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A Scene is Worth a Thousand Features: Feed-Forward Camera Localization from a Collection of Image Features
FastForward represents scenes as collections of 3D-anchored image features and performs camera pose estimation via feed-forward correspondence prediction, achieving competitive accuracy with minimal mapping time.
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VGGT-SLAM: Dense RGB SLAM Optimized on the SL(4) Manifold
VGGT-SLAM aligns VGGT submaps via SL(4) manifold optimization of 15-DoF homographies to enable consistent dense RGB SLAM on long uncalibrated monocular videos.
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Privacy-Preserving Structureless Visual Localization via Image Obfuscation
Simple image obfuscation enables privacy-preserving structureless visual localization with standard feature matchers and no pipeline changes, achieving state-of-the-art accuracy among privacy methods.
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TTT3R: 3D Reconstruction as Test-Time Training
TTT3R derives a closed-form learning rate from memory-observation alignment confidence to boost length generalization in RNN-based 3D reconstruction by 2x in global pose estimation.