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GraspNet: A Large-Scale Clustered and Densely Annotated Dataset for Object Grasping

, , , and . (2019)cite arxiv:1912.13470Comment: Report for our recent work.

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AnyGrasp: Robust and Efficient Grasp Perception in Spatial and Temporal Domains., , , , , , , , and . IEEE Trans. Robotics, 39 (5): 3929-3945 (October 2023)Graspness Discovery in Clutters for Fast and Accurate Grasp Detection., , , , , and . ICCV, page 15944-15953. IEEE, (2021)RGB Matters: Learning 7-DoF Grasp Poses on Monocular RGBD Images., , , , , and . ICRA, page 13459-13466. IEEE, (2021)Target-referenced Reactive Grasping for Dynamic Objects., , , , , , , , and . CVPR, page 8824-8833. IEEE, (2023)Unseen Object 6D Pose Estimation: A Benchmark and Baselines., , , , , and . CoRR, (2022)GraspNet: A Large-Scale Clustered and Densely Annotated Dataset for Object Grasping, , , and . (2019)cite arxiv:1912.13470Comment: Report for our recent work.InstaBoost++: Visual Coherence Principles for Unified 2D/3D Instance Level Data Augmentation., , , , , and . Int. J. Comput. Vis., 131 (10): 2665-2681 (October 2023)GraspNet: A Large-Scale Clustered and Densely Annotated Datase for Object Grasping., , , and . CoRR, (2019)A Real World Dataset for Multi-view 3D Reconstruction., , , , and . ECCV (8), volume 13668 of Lecture Notes in Computer Science, page 56-73. Springer, (2022)AnyGrasp: Robust and Efficient Grasp Perception in Spatial and Temporal Domains., , , , , , , , and . CoRR, (2022)