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arXiv Computer Vision By Vincent Leroy, Philippe Weinzaepfel, Lojze Zust, Yohann Cabon, J\'erome Revaud

BLASt3R: Bundle Adjustment of Any Image Set with Multi-View Matching and Monocular Priors

Read the original on arXiv Computer Vision →

BLASt3R presents a regularized bundle adjustment framework that combines a fast multi‑view matcher with monocular priors for initialization and regularization. The method unifies online Visual SLAM and offline reconstruction from unordered image collections, using a single optimization pipeline and shared hyperparameters. Experiments show that BLASt3R improves performance and speed tradeoffs compared to traditional, feed‑forward, and hybrid baselines, and its uncalibrated VSLAM variant surpasses all previous calibrated approaches.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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