Xinyang Lu, Shengzhe Wei, Sheng Tang, Weiqi Zhang, Juntong Fang, Zesong Li · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31321 · open-access PDF
Penyesuaian fitur lokal biasanya dirumuskan untuk pasangan gambar, meskipun struktur-from-motion dan lokalisasi visual umumnya cocok satu gambar referensi terhadap banyak tetangga yang ditemukan atau dapat dilihat. Mengaplikasikan pasangan matcher secara independen ke tepi-tepi tetangga pusat ini menggandakan perhitungan sisi referensi dan mencegah matcher memanfaatkan bukti geometris multi-view yang melengkapi dari pengamatan yang tersisa. Untuk mengatasi keterbatasan ini, kami memperkenalkan MVLoMa, matcher bintang-graf yang langka yang memperluas LoMa dari pasangan gambar ke banyak tampilan. MVLoMa pertama menggunakan multi-vi beku
Machine translation (Meta M2M100); the English original follows.
Local feature matching is typically formulated for image pairs, although structure-from-motion and visual localization commonly match one reference image against many retrieved or covisible neighbours. Applying a pairwise matcher independently to these centre-neighbour edges duplicates reference-side computation and prevents the matcher from exploiting complementary multi-view geometric evidence from the remaining observations. To address these limitations, we introduce MVLoMa, a sparse star-graph matcher that extends LoMa from image pairs to multiple views. MVLoMa first uses a frozen multi-vi
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