BOP: Benchmark for 6D Object Pose Estimation |
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29/May/2024 - BOP Challenge 2024 has been opened!
18/Apr/2024 - The BOP datasets are now hosted on BOP HuggingFace Hub to prevent bandwidth overload and BOP website crashes.
04/Apr/2024 - BOP Challenge 2023 report has been accepted to the Workshop on Computer Vision for Mixed Reality at CVPR 2024.
03/Oct/2023 - Winners of the BOP Challenge 2023 have been announced at the R6D workshop at ICCV 2023 (results, recording). Congratulations!
26/Sep/2023 - The submission deadline for BOP Challenge 2023 is extended to September 28, 9:00AM UTC.
07/Jun/2023 - BOP Challenge 2023 has been opened!
26/May/2023 - Raw results from all public submissions are now available for download (example). This allows anyone to analyze individual methods in more detail.
05/Apr/2023 - BOP Challenge 2022 report has been accepted to the Workshop on Computer Vision for Mixed Reality at CVPR 2023.
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 an 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!
Join the BOP Google group to stay up to date. IntroductionThe 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. PublicationsT. Hoda艌, M. Sundermeyer, Y. Labb茅, V. N. Nguyen, G. Wang, E. Brachmann, B. Drost, V. Lepetit, C. Rother, J. Matas, BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of Seen and Unseen Rigid Objects IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW, CV4MR workshop) 2024, Seattle. [PDF, SLIDES, VIDEO, BIB] M. Sundermeyer, T. Hoda艌, Y. Labb茅, G. Wang, E. Brachmann, B. Drost, C. Rother, J. Matas, BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW, CV4MR workshop) 2023, Vancouver. [PDF, SLIDES, VIDEO 1, VIDEO 2, BIB] T. Hoda艌, M. Sundermeyer, B. Drost, Y. Labb茅, 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. Hoda艌, 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. Hoda艌 and A. Melenovsk媒. BOP toolkitDownload the BOP toolkit with python scripts for reading the standard dataset format, rendering, evaluation etc. Contact |
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