- Author: Allen Institute for AI / University of Washington
- paper: https://arxiv.org/abs/2104.11213v1
这项工作提出了全流双向融合FFB6D网络,根据单个RGBD图像进行6D姿态估计,利用RGB图像中的外观信息和深度图像中的几何信息作为两个互补的数据源,将視覺和几何信息结合,以进行更好的表示学习。在多个数据集上都达到了SOTA!
- Author: Hong Kong University of Science and Technology / Megvii Technology / Kuaishou Technology
- Paper: https://arxiv.org/abs/2103.02242v1
- Code: https://github.com/ethnhe/FFB6D
- Author: Tsinghua University, BNRist / Technical University of Munich / Google
- Paper: https://arxiv.org/abs/2102.12145v3
- Code: https://github.com/THU-DA-6D-Pose-Group/GDR-Net
FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism - oral
- Author: , University of Birmingham / Shenzhen University
- Paper: https://arxiv.org/abs/2103.07054v1
- Code: https://github.com/DC1991/FS-Net
- Author: EPFL Computer Vision Lab / EPFL Realistic Graphics Lab / ClearSpace SA
- Paper: https://arxiv.org/abs/2104.00337v1
- Author: Baidu Research / ReLER, University of Technology Sydney
- Paper: https://arxiv.org/abs/2104.03658v1
- Author: ENS Inria / LIGM, ENPC / CIIRC CTU
- HomePage: https://www.di.ens.fr/willow/research/robopose/
- Paper: https://arxiv.org/abs/2104.09359v1