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IFOR: Iterative Flow Minimization for Robotic Object Rearrangement

  • Published:2022-06 Issue: Volume: Page:
  • ISSN:
  • Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • language:
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Author:

Goyal Ankit1,Mousavian Arsalan1,Paxton Chris1,Chao Yu-Wei1,Okorn Brian1,Deng Jia2,Fox Dieter1

Affiliation:

1. NVIDIA

2. Princeton University

Publisher

IEEE

Reference74 articles.

1. Separable flow: Learning motion cost volumes for optical flow estimation;feihu;ICCV,2021

2. Transporter networks: Rearranging the visual world for robotic manipulation;zeng;CARl,2020

3. Learning to Find Good Correspondences

4. Learning RGB- D feature embeddings for unseen object instance segmentation;xiang;CARl,2020

5. Patch2Pix: Epipolar-Guided Pixel-Level Correspondences

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1. Efficient Object Rearrangement via Multi-view Fusion;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

2. Mean Shift Mask Transformer for Unseen Object Instance Segmentation;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. SG-Bot: Object Rearrangement via Coarse-to-Fine Robotic Imagination on Scene Graphs;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. Neural Rearrangement Planning for Object Retrieval from Confined Spaces Perceivable by Robot’s In-hand RGB-D Sensor;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

5. Everyday Objects Rearrangement in a Human-Like Manner via Robotic Imagination and Learning From Demonstration;IEEE Access;2024
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