[HTML][HTML] Indoor synthetic data generation: A systematic review
Objective: Deep learning-based object recognition, 6D pose estimation, and semantic scene
understanding require a large amount of training data to achieve generalization. Time …
understanding require a large amount of training data to achieve generalization. Time …
Human action recognition in drone videos using a few aerial training examples
Drones are enabling new forms of human actions surveillance due to their low cost and fast
mobility. However, using deep neural networks for automatic aerial action recognition is …
mobility. However, using deep neural networks for automatic aerial action recognition is …
Real-time and efficient 6-D pose estimation from a single RGB image
6-D pose estimation is an important branch in the field of vision measurement and is widely
used in the fields of robotics, autonomous driving, and reality augmentation. The latest …
used in the fields of robotics, autonomous driving, and reality augmentation. The latest …
Gq-stn: Optimizing one-shot grasp detection based on robustness classifier
A Gariépy, JC Ruel, B Chaib-Draa… - 2019 IEEE/RSJ …, 2019 - ieeexplore.ieee.org
Gras** is a fundamental robotic task needed for the deployment of household robots or
furthering warehouse automation. However, few approaches are able to perform grasp …
furthering warehouse automation. However, few approaches are able to perform grasp …
MFPN-6D: Real-time one-stage pose estimation of objects on RGB images
6D pose estimation of objects is an important part of robot gras**. The latest research
trend on 6D pose estimation is to train a deep neural network to directly predict the 2D …
trend on 6D pose estimation is to train a deep neural network to directly predict the 2D …
[PDF][PDF] Cps: Class-level 6d pose and shape estimation from monocular images
F Manhardt, M Nickel, S Meier… - ar** skills learned from a simulator to the real world is beneficial in
reducing the cost of labeling. However, the models trained on synthetic data are brittle when …
reducing the cost of labeling. However, the models trained on synthetic data are brittle when …
GSNet: Model reconstruction network for category-level 6d object pose and size estimation
Category-level 6D pose and size estimation is to estimate the rotation, translation and size of
the observed instance objects from an arbitrary angle in a cluttered scene. Compared with …
the observed instance objects from an arbitrary angle in a cluttered scene. Compared with …
3D object detection and 6D pose estimation using RGB-D images and mask R-CNN
HY Lin - 2020 IEEE International Conference on Fuzzy …, 2020 - ieeexplore.ieee.org
Understanding 3D scenes have attracted significant interests in recent years. Specifically, it
is used with visual sensors to provide the information for a robotic manipulator to interact …
is used with visual sensors to provide the information for a robotic manipulator to interact …
Visual Attention and Color Cues for 6D Pose Estimation on Occluded Scenarios Using RGB-D Data
J Vidal, CY Lin, R Martí - Sensors, 2021 - mdpi.com
Recently, 6D pose estimation methods have shown robust performance on highly cluttered
scenes and different illumination conditions. However, occlusions are still challenging, with …
scenes and different illumination conditions. However, occlusions are still challenging, with …