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Perception for Grasping and Manipulation I

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Paper List

  • I2c-Net: Using Instance-Level Neural Networks for Monocular Category-Level 6D Pose Estimation [Abstract]

  • Self-Supervised Instance Segmentation by Grasping [Abstract]

  • Fusing Visual Appearance and Geometry for Multi-Modality 6DoF Object Tracking [Abstract]

  • Viewpoint Push Planning for Mapping of Unknown Confined Spaces [Abstract]

  • Depth-Based 6DoF Object Pose Estimation Using Swin Transformer [Abstract]

  • DR-Pose: A Two-Stage Deformation-And-Registration Pipeline for Category-Level 6D Object Pose Estimation [Abstract]

  • Learning from Pixels with Expert Observations [Abstract]

  • RMBench: Benchmarking Deep Reinforcement Learning for Robotic Manipulator Control [Abstract]

  • Shape Completion with Prediction of Uncertain Regions [Abstract]

  • Structure from Action: Learning Interactions for 3D Articulated Object Structure Discovery [Abstract]

  • Object-Oriented Option Framework for Robotics Manipulation in Clutter [Abstract]

  • Non-Contact Tactile Perception for Hybrid-Active Gripper [Abstract]