24/7 Place Recognition by View Synthesis


Example query images from the newly collected 24/7 Tokyo dataset. Each place in the query set is captured at different times of day: (a) daytime, (b) sunset, and (c) night. For comparison, the database street-view image at a close-by position is shown in (d). Note the major changes in appearance (illumination changes in the scene) between the database image (d) and the query images (a,b,c).

Authors: Akihiko Torii, Relja Arandjelović, Josef SivicMasatoshi Okutomi, Tomas Pajdla

Akihiko Torii, Relja Arandjelović, Josef Sivic, Masatoshi Okutomi, Tomas Pajdla.
24/7 place recognition by view synthesis.

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.

author = {Torii, A. and Arandjelovi\'c, R. and Sivic, J. and Okutomi, M. and Pajdla, T.},
title = {24/7 place recognition by view synthesis},
booktitle = {CVPR},
year = {2015},

Code: Code (dense VLAD description, feature matching, view synthesis) (1.1GB).  (ver01 08/06/2015)


Query images (4.1GB). (ver 01 08/06/2015)

Query images (4.1GB). (ver 02 20/06/2015) (UTM added in csv files)

Query images (4.1GB). (ver 03 21/09/2015) (GPS, UTM of 0757-0765 were corrected. These images did not appear in our CVPR 2015 paper.)

Query images - subset used in our CVPR 2015 paper - (1.1GB).

Funding: This work was partly supported by JSPS KAKENHI Grant Number 24700161, EU FP7-SPACE-2012-312377 PRoViDE, the ERC grant LEAP (no. 336845), ANR project Semapolis (ANR-13-CORD-0003) and the Intelligence Advanced Research Projects Activity (IARPA) via Air Force Research Laboratory, contract FA8650-12-C-7212. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, AFRL, or the U.S. Government.

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