Image-based Localization using Hourglass Networks

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Tutkijat

Organisaatiot

  • Tampere University of Technology

Kuvaus

In this paper, we propose an encoder-decoder convolutional neural network (CNN) architecture for estimating camera pose (orientation and location) from a single RGB image. The architecture has a hourglass shape consisting of a chain of convolution and up-convolution layers followed by a regression part. The up-convolution layers are introduced to preserve the fine-grained information of the input image. Following the common practice, we train our model in end-to-end manner utilizing transfer learning from large scale classification data. The experiments demonstrate the performance of the approach on data exhibiting different lighting conditions, reflections, and motion blur. The results indicate a clear improvement over the previous state-of-theart even when compared to methods that utilize sequence of test frames instead of a single frame.

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
TilaJulkaistu - 2017
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Computer Vision - Venice, Italia
Kesto: 22 lokakuuta 201729 lokakuuta 2017

Julkaisusarja

NimiIEEE International Conference on Computer Vision workshops
KustantajaIEEE
ISSN (painettu)2473-9936
ISSN (elektroninen)2473-9944

Conference

ConferenceInternational Conference on Computer Vision
LyhennettäICCV
MaaItalia
KaupunkiVenice
Ajanjakso22/10/201729/10/2017

ID: 16829464