mlsanityData to 7 Oct 2026

REGRAD: A Large-Scale Relational Grasp Dataset for Safe and Object-Specific Robotic Grasping in Clutter

arXiv 2104.14118 ↗First posted 29 Apr 2021cs.RO cs.CVcited by 11

Not on the map. Why?

Abstract (arXiv)

Despite the impressive progress achieved in robotic grasping, robots are not skilled in sophisticated tasks (e.g. search and grasp a specified target in clutter). Such tasks involve not only grasping but the comprehensive perception of the world (e.g. the object relationships). Recently, encouraging results demonstrate that it is possible to understand high-level concepts by learning. However, such algorithms are usually data-intensive, and the lack of data severely limits their performance. In this paper, we present a new dataset named REGRAD for the learning of relationships among objects and grasps. We collect the annotations of object poses, segmentations, grasps, and relationships for the target-driven relational grasping tasks. Our dataset is collected in both forms of 2D images and 3D point clouds. Moreover, since all the data are generated automatically, it is free to import new objects for data generation. We also released a real-world validation dataset to evaluate the sim-to-real performance of models trained on REGRAD. Finally, we conducted a series of experiments, showing that the models trained on REGRAD could generalize well to the realistic scenarios, in terms of both relationship and grasp detection. Our dataset and code could be found at: https://github.com/poisonwine/REGRAD

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 54 of its 103 references that are in the map. First posted on arXiv 29 Apr 2021.

Builds on

54 of 103 references.

References · 54

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  3. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  4. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  5. 2016Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotationscited by 2,646
  6. 2017Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real Worldcited by 1,401
  7. 2017Adversarial Discriminative Domain Adaptationcited by 1,309
  8. 2020PCT: Point cloud transformercited by 730
  9. 2017Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithmcited by 723
  10. 2018Deep Visual Domain Adaptation: A Surveycited by 634
  11. 2020SAPIEN: A SimulAted Part-based Interactive ENvironmentcited by 584
  12. 2019Contrastive Adaptation Network for Unsupervised Domain Adaptationcited by 407
38 more
  1. 2016Visual Relationship Detection with Language Priorscited by 333
  2. 2016Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collectioncited by 312
  3. 2017Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metricscited by 259
  4. 2019Adversarial Domain Adaptation with Domain Mixupcited by 250
  5. 20196-DOF GraspNet: Variational Grasp Generation for Object Manipulationcited by 237
  6. 2015Supersizing Self-supervision: Learning to Grasp from 50K Tries and 700 Robot Hourscited by 208
  7. 2018Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experiencecited by 203
  8. 2018Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networkscited by 171
  9. 2017Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Graspingcited by 138
  10. 2018Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learningcited by 121
  11. 2018Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approachcited by 117
  12. 2013Deep Learning for Detecting Robotic Graspscited by 114
  13. 2017Visual Translation Embedding Network for Visual Relation Detectioncited by 112
  14. 2020CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistencycited by 107
  15. 2013Data-Driven Grasp Synthesis - A Surveycited by 104
  16. 2020Deep Visual Domain Adaptationcited by 91
  17. 2016Sim-to-Real Robot Learning from Pixels with Progressive Netscited by 89
  18. 2018Jacquard: A Large Scale Dataset for Robotic Grasp Detectioncited by 86
  19. 2018PointNetGPD: Detecting Grasp Configurations from Point Setscited by 80
  20. 2014Real-Time Grasp Detection Using Convolutional Neural Networkscited by 75
  21. 2016Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challengecited by 70
  22. 20196-DOF Grasping for Target-driven Object Manipulation in Cluttercited by 70
  23. 2019ShapeGlot: Learning Language for Shape Differentiationcited by 54
  24. 2019S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenescited by 51
  25. 2016Robotic Grasp Detection using Deep Convolutional Neural Networkscited by 47
  26. 2020PointNet++ Grasping: Learning An End-to-end Spatial Grasp Generation Algorithm from Sparse Point Cloudscited by 39
  27. 2021Contrastive Domain Adaptationcited by 36
  28. 2017Multi-Task Domain Adaptation for Deep Learning of Instance Grasping from Simulationcited by 35
  29. 2020A Boundary Based Out-of-Distribution Classifier for Generalized Zero-Shot Learningcited by 34
  30. 2016High precision grasp pose detection in dense cluttercited by 33
  31. 2018ROI-based Robotic Grasp Detection for Object Overlapping Scenescited by 31
  32. 2021Domain Adaptation for Semantic Segmentation via Patch-Wise Contrastive Learningcited by 30
  33. 2017End-to-End Learning of Semantic Graspingcited by 20
  34. 2017Intention-Net: Integrating Planning and Deep Learning for Goal-Directed Autonomous Navigationcited by 19
  35. 2019LeTS-Drive: Driving in a Crowd by Learning from Tree Searchcited by 13
  36. 2018Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Featurescited by 11
  37. 2018Visual Manipulation Relationship Networkcited by 10
  38. 2020Grasping Detection Network with Uncertainty Estimation for Confidence-Driven Semi-Supervised Domain Adaptationcited by 9

50 most cited of 54 All 54 (JSON)

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 3; 2025: 4.

11 papers.

  1. 2022MetaGraspNet: A Large-Scale Benchmark Dataset for Scene-Aware Ambidextrous Bin Picking via Physics-based Metaverse Synthesiscited by 13
  2. 2025ZeroGrasp: Zero-Shot Shape Reconstruction Enabled Robotic Graspingcited by 13
  3. 2023RGB-D Grasp Detection via Depth Guided Learning with Cross-modal Attentioncited by 9
  4. 2025Free-form language-based robotic reasoning and graspingcited by 8
  5. 2024Sim-to-Real Grasp Detection with Global-to-Local RGB-D Adaptationcited by 4
  6. 2021MetaGraspNet_v0: A Large-Scale Benchmark Dataset for Vision-driven Robotic Grasping via Physics-based Metaverse Synthesiscited by 2
  7. 2024A Modern Take on Visual Relationship Reasoning for Grasp Planningcited by 2
  8. 2023MMRDN: Consistent Representation for Multi-View Manipulation Relationship Detection in Object-Stacked Scenescited by 1
  9. 2025Obstruction reasoning for robotic graspingcited by 1
  10. 2025ViTA-Seg: Vision Transformer for Amodal Segmentation in Roboticscited by 1
  11. 20243D Feature Distillation with Object-Centric Priorscited by 0