DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion ForrestDing 827 1 【论文研读】5. 从图像视频提取3D人体模型的深度学习现状|3D Human Pose Estimation BingPanda 630 0 【 计算机视觉 】Object detection YOLO/SSD MASK/Faster RCNN 演示(inferense)视频 贝叶斯派对 2.2万 34 【CVPR 实时...
SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again—2017(笔记),程序员大本营,技术文章内容聚合第一站。
In the task of 6D pose estimation by RGB-D image, the crucial problem is how to make the most of two types of features respectively from RGB and depth input. As far as we know, prior approaches treat those two sources equally, which may overlook that the different combinations of those ...
Recently, various methods for 6D pose and shape estimation of objects at a per-category level have been proposed. This work provides an overview of the field in terms of methods, datasets, and evaluation protocols. First, an overview of existing works and their commonalities and differences is ...
Therefore, various synthetic datasets were proposed in research works for 6D pose estimation including Unreal Rendered Spacecraft On-Orbit (URSO) dataset29 and Spacecraft pose estimation dataset (SPEED)30,31. In addition to the cost of space data acquisition, object tracking is a complex task ...
Context-aware 6D pose estimation of known objects using RGB-D data RGB-DDeep learningIterative refinement6D pose estimationIn the realm of computer vision and robotics, the pursuit of intelligent robotic grasping and accurate... A Kumar,P Shukla,V Kushwaha,... - 《Multimedia Tools & Application...
place at the Amazon Picking Challenge 2016. Includes RGB-D Realsense sensor drivers (standalone and ROS package), deep learning ROS package for 2D object segmentation (training and testing), ROS package for 6D pose estimation. This is the reference implementation of models and code for our ...
These boxes can then be used to find more attributes like the color, materials, a text description of the object, and the 6D pose of the object. We focus on 6D pose estimation. Thus, for the prediction phase in our approach, we use the ground-truth boxes and the transparency-aware ...
Our network directly outputs the 6D pose without requiring multiple stages or additional post-processing such as a Perspective-n-Point (PnP). The two-stage CNN architecture and our loss function render multi-task joint training effective and efficient. We improve the pose estimation accuracy by ...
Deep-6DPose: Recovering 6D Object Pose from a Single RGB Image. arXiv 2018, arXiv:1802.10367. [Google Scholar] Xiang, Y.; Schmidt, T.; Narayanan, V.; Fox, D. PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes. In Proceedings of the Robotics: ...