GraspNeRF: Multiview-based 6-DoF Grasp Detection for Transparent and Specular Objects Using Generalizable NeRF

Author:

Dai Qiyu1,Zhu Yan1,Geng Yiran1,Ruan Ciyu2,Zhang Jiazhao1,Wang He1

Affiliation:

1. Peking University,Center on Frontiers of Computing Studies

2. College of Intelligence Science and Technology, National University of Defense Technology

Publisher

IEEE

Reference25 articles.

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2. Evo-neRF: Evolving neRF for sequential robot grasping;kerr;6th Annual Conference on Robot Learning,0

3. Neural Rays for Occlusion-aware Image-based Rendering

4. Mvs-nerf: Fast generalizable radiance field reconstruction from multi-view stereo;chen;Proceedings of the IEEE/CVF International Conference on Computer Vision,2021

5. Nerf: Representing scenes as neural radiance fields for view synthesis;mildenhall;ECCV,2020

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1. Multimodal 3D measurement setup for generating multimodal real-world data sets for AI-based transparent object recognition;Dimensional Optical Metrology and Inspection for Practical Applications XIII;2024-06-07

2. RGBGrasp: Image-Based Object Grasping by Capturing Multiple Views During Robot arm Movement With Neural Radiance Fields;IEEE Robotics and Automation Letters;2024-06

3. Efficient End-to-End Detection of 6-DoF Grasps for Robotic Bin Picking;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. STOPNet: Multiview-based 6-DoF Suction Detection for Transparent Objects on Production Lines;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

5. Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

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