- 23/Oct/2022 - Winners of the BOP Challenge 2022 have been announced at the R6D workshop at ECCV 2022 (results, recording: part 1, part 2). Congratulations!!!
- 20/Sep/2022 - Reality Labs at Meta and Niantic donated $4000 in total for BOP Challenge 2022 award money.
- 24/Jul/2022 - Call for papers: R6D workshop at ECCV 2022, submission deadline: August 8.
- 01/May/2022 - BOP Challenge 2022 has been opened!
- 11/Sep/2021 - HOPE, a new dataset from NVIDIA for pose estimation of household objects, has been released.
- 15/Sep/2020 - An analysis of the BOP Challenge 2020 results is now available in this ECCVW 2020 paper.
- 23/Aug/2020 - Winners of the BOP Challenge 2020 have been announced at the R6D workshop at ECCV 2020.
- 09/Jun/2020 - The complete HomebrewedDB dataset is now available in the BOP format.
- 05/Jun/2020 - BOP Challenge 2020 has been opened!
- 27/Jan/2020 - Submissions to the BOP Challenge 2019 have been re-evaluated.
- 28/Oct/2019 - Winners of the BOP Challenge 2019 have been announced.
- 14/Aug/2019 - YCB-Video dataset is now available in the BOP format.
Join the BOP Google group to stay up to date.
Introduction
The goal of BOP is to capture the state of the art in estimating the 6D pose, i.e. 3D translation and 3D rotation, of rigid objects from RGB/RGB-D images. An accurate, fast, robust, scalable and easy-to-train method that solves this task will have a big impact in application fields such as robotics or augmented reality.
Publications
T. Hodaň,
M. Sundermeyer,
B. Drost,
Y. Labbé,
E. Brachmann,
F. Michel,
C. Rother,
J. Matas,
BOP Challenge 2020 on 6D Object Localization,
European Conference on Computer Vision Workshops (ECCVW) 2020, Glasgow.
[PDF,
SLIDES,
BIB]
T. Hodaň,
F. Michel,
E. Brachmann,
W. Kehl,
A. G. Buch,
D. Kraft,
B. Drost,
J. Vidal,
S. Ihrke,
X. Zabulis,
C. Sahin,
F. Manhardt,
F. Tombari,
T.-K. Kim,
J. Matas,
C. Rother,
BOP: Benchmark for 6D Object Pose Estimation,
European Conference on Computer Vision (ECCV) 2018, Munich.
[PDF,
SLIDES,
POSTER,
BIB]
The online evaluation system has been developed by T. Hodaň and A. Melenovský.
BOP toolkit
Download the BOP toolkit with python scripts for reading the standard dataset format, rendering, evaluation etc.