mlsanityData to 7 Oct 2026

CenterArt: Joint Shape Reconstruction and 6-DoF Grasp Estimation of Articulated Objects

arXiv 2404.14968 ↗First posted 23 Apr 2024cs.RO cs.CVcited by 1

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Abstract (arXiv)

Precisely grasping and reconstructing articulated objects is key to enabling general robotic manipulation. In this paper, we propose CenterArt, a novel approach for simultaneous 3D shape reconstruction and 6-DoF grasp estimation of articulated objects. CenterArt takes RGB-D images of the scene as input and first predicts the shape and joint codes through an encoder. The decoder then leverages these codes to reconstruct 3D shapes and estimate 6-DoF grasp poses of the objects. We further develop a mechanism for generating a dataset of 6-DoF grasp ground truth poses for articulated objects. CenterArt is trained on realistic scenes containing multiple articulated objects with randomized designs, textures, lighting conditions, and realistic depths. We perform extensive experiments demonstrating that CenterArt outperforms existing methods in accuracy and robustness.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 23 of its 25 references that are in the map. First posted on arXiv 23 Apr 2024.

Builds on

23 of 25 references.

References · 23

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  3. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  4. 2019Objects as Pointscited by 1,172
  5. 2019Panoptic Feature Pyramid Networkscited by 644
  6. 2020SAPIEN: A SimulAted Part-based Interactive ENvironmentcited by 584
  7. 2018PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understandingcited by 521
  8. 2021Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenescited by 213
  9. 2021Where2Act: From Pixels to Actions for Articulated 3D Objectscited by 179
  10. 2021A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representationcited by 113
  11. 2022CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimationcited by 69
  12. 2024Language-Grounded Dynamic Scene Graphs for Interactive Object Search with Mobile Manipulationcited by 69
11 more
  1. 2021UMPNet: Universal Manipulation Policy Network for Articulated Objectscited by 64
  2. 2023CARTO: Category and Joint Agnostic Reconstruction of ARTiculated Objectscited by 64
  3. 2023FlowBot++: Learning Generalized Articulated Objects Manipulation via Articulation Projectioncited by 34
  4. 2022Neural Grasp Distance Fields for Robot Manipulationcited by 31
  5. 2022Category-Independent Articulated Object Tracking with Factor Graphscited by 24
  6. 2021SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereocited by 18
  7. 2022Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulationcited by 15
  8. 2023CenterGrasp: Object-Aware Implicit Representation Learning for Simultaneous Shape Reconstruction and 6-DoF Grasp Estimationcited by 13
  9. 2023Learning Hierarchical Interactive Multi-Object Search for Mobile Manipulationcited by 12
  10. 2023Online Estimation of Articulated Objects with Factor Graphs using Vision and Proprioceptive Sensingcited by 10
  11. 2020Kineverse: A Symbolic Articulation Model Framework for Model-Agnostic Mobile Manipulationcited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026ArtHOI: Taming Foundation Models for Monocular 4D Reconstruction of Hand-Articulated-Object Interactionscited by 3