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Image Matching across Wide Baselines: From Paper to Practice

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00342509" target="_blank" >RIV/68407700:21230/21:00342509 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/s11263-020-01385-0" target="_blank" >https://doi.org/10.1007/s11263-020-01385-0</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s11263-020-01385-0" target="_blank" >10.1007/s11263-020-01385-0</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Image Matching across Wide Baselines: From Paper to Practice

  • Original language description

    We introduce a comprehensive benchmark for local features and robust estimation algorithms, focusing on the downstream task -- the accuracy of the reconstructed camera pose -- as our primary metric. Our pipeline's modular structure allows easy integration, configuration, and combination of different methods and heuristics. This is demonstrated by embedding dozens of popular algorithms and evaluating them, from seminal works to the cutting edge of machine learning research. We show that with proper settings, classical solutions may still outperform the perceived state of the art. Besides establishing the actual state of the art, the conducted experiments reveal unexpected properties of Structure from Motion (SfM) pipelines that can help improve their performance, for both algorithmic and learned methods. Data and code are online https://github.com/team-yi-ubc/image-matching-benchmark providing an easy-to-use and flexible framework for the benchmarking of local features and robust estimation methods, both alongside and against top-performing methods. This work provides a basis for the Image Matching Challenge https://vision.uvic.ca/image-matching-challenge/.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    International Journal of Computer Vision

  • ISSN

    0920-5691

  • e-ISSN

    1573-1405

  • Volume of the periodical

    129

  • Issue of the periodical within the volume

    February

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    31

  • Pages from-to

    517-547

  • UT code for WoS article

    000577443300001

  • EID of the result in the Scopus database

    2-s2.0-85092220167