Efficient Fully Convolution Neural Network for Generating Pixel Wise Robotic Grasps With High Resolution Images
Explore this paper's citation graph
- Type
- preprint
- Published
- 2019-02-24
- Cited by
- 44
- References
- 28
- Access
- Open access
- OpenAlex
- https://openalex.org/W2916725700
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:67856132
Keywords
Artificial intelligence, Pixel, Computer science, Computer vision, GRASP
References
- Robotic grasping and contact: a review
- Real-time grasp detection using convolutional neural networks
- Fully convolutional networks for semantic segmentation
- Template-based learning of grasp selection
- Robot Grasp Synthesis Algorithms: A Survey
- Deep learning for detecting robotic grasps
- An overview of 3D object grasp synthesis algorithms
- Data-Driven Grasp Synthesis—A Survey
- Robotic Grasping of Novel Objects using Vision
- Automatic grasp planning using shape primitives
- Efficient grasping from RGBD images: Learning using a new rectangle representation
- Robotic grasp detection using deep convolutional neural networks
- Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics
- Robust Robot Grasp Detection in Multimodal Fusion
- Classification based Grasp Detection using Spatial Transformer Network
- Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach
- Review of Deep Learning Methods in Robotic Grasp Detection
- GraspNet: An Efficient Convolutional Neural Network for Real-time Grasp Detection for Low-powered Devices
- Real-World Multiobject, Multigrasp Detection
- Real-Time, Highly Accurate Robotic Grasp Detection using Fully Convolutional Neural Networks with High-Resolution Images
Cited by
- Generative Attention Learning: a “GenerAL” framework for high-performance multi-fingered grasping in clutter
- Event-based Robotic Grasping Detection with Neuromorphic Vision Sensor and Event-Stream Dataset
- Orientation Attentive Robot Grasp Synthesis
- Visuo-Haptic Grasping of Unknown Objects through Exploration and Learning on Humanoid Robots
- Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review
- Event-Based Robotic Grasping Detection With Neuromorphic Vision Sensor and Event-Grasping Dataset
- Comprehensive Review on Reaching and Grasping of Objects in Robotics
- Residual Squeeze-and-Excitation Network with Multi-scale Spatial Pyramid Module for Fast Robotic Grasping Detection
- ADFNet: A two-branch robotic grasping network based on attention mechanism
- PEGG-Net: Background Agnostic Pixel-Wise Efficient Grasp Generation Under Closed-Loop Conditions
- A Vision-Based Robot Grasping System
- A Novel Generative Convolutional Neural Network for Robot Grasp Detection on Gaussian Guidance
- NeuroGrasp: Multimodal Neural Network With Euler Region Regression for Neuromorphic Vision-Based Grasp Pose Estimation
- GR-ConvNet v2: A Real-Time Multi-Grasp Detection Network for Robotic Grasping
- Data-driven robotic visual grasping detection for unknown objects: A problem-oriented review
- CGNet: Robotic Grasp Detection in Heavily Cluttered Scenes
- SKGNet: Robotic Grasp Detection With Selective Kernel Convolution
- Efficient Grasp Detection Network With Gaussian-Based Grasp Representation for Robotic Manipulation
- CPQNet: Contact Points Quality Network for Robotic Grasping
- Rotation adaptive grasping estimation network oriented to unknown objects based on novel RGB-D fusion strategy
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