Real-Time Seamless Single Shot 6D Object Pose Prediction We propose a single-shot approach for simultaneously detecting an object in an RGB image and predicting its 6D pose without requiring multiple stages or ha... B Tekin,SN Sinha,P Fua 被引量: 54发表: 2017年 Real-Time Hybrid Pose ...
【6D物体姿态估计】Real-Time 6D Object Pose Estimation on CPU 本文来自欧姆龙和中京大学,论文关注的问题是实时 6D 物体姿态估计。作者提出了一个基于 model 的匹配算法,效果卓越。在 CPU 上就可以达到实时,...
Real-Time Seamless Single Shot 6D Object Pose Prediction Bugra Tekin, Sudipta Sinha, Pascal Fua IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018|June 2018 arXiv Download BibTex We propose a single-shot approach for simultaneously detecting an object in an RGB image and ...
Our system is accurate and fast (10 fps), which is well suited for real-time applications. In particular, LieNet detects and segments object instances in the image analogous to modern instance segmentation networks such as Mask R-CNN, but contains a novel additional sub-network for 6D pose ...
suuman / singleshotpose Public forked from microsoft/singleshotpose Notifications Fork 0 Star 0 This research project implements a real-time object detection and pose estimation method as described in the paper, Tekin et al. "Real-Time Seamless Single Shot 6D Object Pose Prediction", CVPR ...
The huge amount of literature on real-time object tracking continuously reports good results with respect to accuracy and robustness. However, when it come
This research project implements a real-time object detection and pose estimation method as described in the paper, Tekin et al. "Real-Time Seamless Single Shot 6D Object Pose Prediction", CVPR 2018. (https://arxiv.org/abs/1711.08848). - scp10086/singles
The objective of human pose estimation (HPE) derived from deep learning aims to accurately estimate and predict the human body posture in images or videos via the utilization of deep neural networks. However, the accuracy of real-time HPE tasks is still
error w.r.t the real travelled distance; and latency which measures the time from receiving the inertia measurements to outputting the pose and translation for the correspond- ing frame in ms, using a laptop with an Intel(R) Core(TM) i7-10750H CP...
Keywords: pose estimation; real-time; perception; point cloud 1. Introduction In field robotics, estimating the pose (position and orientation) of known geometries within point cloud data is a common challenge. The motivation is to provide robotic agents with the perceptual information to detect and...