Rother, "BOP: Benchmark for 6D Object Pose Estimation", ECCV, 2018T. Hodan, 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. Kim, J. Matas, and C. Rother. BOP: benchmark ...
BOP: Benchmark for 6D Object Pose EstimationTomᡠs Hodaˇ n 1∗ , Frank Michel 2∗ , Eric Brachmann 3 , Wadim Kehl 4Anders Glent Buch 5 , Dirk Kraft 5 , Bertram Drost 6 , Joel Vidal 7 , Stephan Ihrke 2Xenophon Zabulis 8 , Caner Sahin 9 , Fabian Manhardt 10 , Federico ...
BOP: Benchmark for 6D Object Pose Estimation 来自 钛学术 喜欢 0 阅读量: 190 作者:T Hodan,F Michel,E Brachmann,W Kehl,C Rother 摘要: We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D ...
A first-reconstruct-then-regress approach for weakly-supervised 6d object pose estimation [...
We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. The benchmark comprises of: i) eight datasets in a unified format that cover diffe...
🗂️ Omni6DPose Dataset Dataset Overview The Omni6DPose dataset is available for download atOmni6DPose. The dataset is organized into four parts: ROPE:the real dataset for evaluation. SOPE:the simulated dataset for training. PAM:the pose aligned 3D models used in both ROPE and SOPE. ...
For 6D pose estimation, [45] contributes a dataset with 21 objects and 92 scenes. These datasets mainly focus on a subarea of grasp pose detection. In this work, we aim to build a dataset that is much larger in scale and diversity and covers main asp...
Kitani. StereOBJ-1M: Large-scale stereo image dataset for 6D object pose estima- tion. CoRR, abs/2109.10115, 2021. 2, 5, 6 [27] Xingyu Liu, Rico Jonschkowski, Anelia Angelova, and Kurt Konolige. KeyPose: Multi-view 3D labeling and keypoint estimation for tra...
ApolloCar3D, which complements existing public 3D object datasets. • A novel evaluation metric, i.e. A3DP, which jointly considers both 3D shape and 3D pose thus is more ap- propriate for the task of 3D instance understanding. • Two baseline algorithms...
6D Object Pose Estimation is a crucial yet challenging task in computer vision, suffering from a significant lack of large-scale datasets. This scarcity impedes comprehensive evaluation of model performance, limiting research advancements. Furthermore, the restricted number of available instances or catego...