6533b826fe1ef96bd128474e
RESEARCH PRODUCT
Which Is Which? Evaluation of Local Descriptors for Image Matching in Real-World Scenarios
Fabio BellaviaCarlo Colombosubject
Matching (statistics)Computer scienceDeep descriptorVisual descriptorsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology010501 environmental sciencesMachine learningcomputer.software_genreCONTEST01 natural sciencesTask (project management)Local image descriptors0202 electrical engineering electronic engineering information engineering0105 earth and related environmental sciencesSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniLocal image descriptors Image matching Deep descriptorsImage matchingSettore INF/01 - Informaticabusiness.industryImage matchingDeep learningBenchmarkingReal image020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerdescription
Matching with local image descriptors is a fundamental task in many computer vision applications. This paper describes the WISW contest held within the framework of the CAIP 2019 conference, aimed at benchmarking recent descriptors in challenging planar and non-planar real image matching scenarios. According to the contest results, the descriptors submitted to the competition, most of which based on deep learning, perform significantly better than the current state-of-the-art in image matching. Nonetheless, there is still room for improvement, especially in the case of non-planar scenes.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-01 |