Alternatives and similar repositories for 6D-CLGrasp

Users that are interested in 6D-CLGrasp are comparing it to the libraries listed below

• CNJianLiu / MH6D
  [TNNLS 2025] Code for "MH6D: Multi-Hypothesis Consistency Learning for Category-Level 6D Object Pose Estimation".
  ☆38Updated last month
• yanjh97 / TransGrasp
  [ECCV 2022] TransGrasp: Grasp Pose Estimation of a Category of Objects by Transferring Grasps from Only One Labeled Instance
  ☆63Updated 2 years ago
• hetolin / SAR-Net
  Code for "SAR-Net: Shape Alignment and Recovery Network for Category-level 6D Object Pose and Size Estimation" CVPR2022
  ☆77Updated last year
• luyh20 / FGC-GraspNet
  ICRA 2022 "Hybrid Physical Metric For 6-DoF Grasp Pose Detection"
  ☆74Updated last year
• rhett-chen / grasp-auto-annotation
  grasp labels auto-annotation
  ☆21Updated last year
• alinasarmiento / pytorch_contactnet
  PyTorch implementation of Contact-GraspNet
  ☆21Updated 2 years ago
• mahaoxiang822 / Generalizing-Grasp
  Official implementation of CVPR2024 paper "Generalizing 6-DoF Grasp Detection via Domain Prior Knowledge"
  ☆49Updated last year
• mahaoxiang822 / Scale-Balanced-Grasp
  Code for CoRL2022 paper "Towards Scale Balanced 6-DoF Grasp Detection in Cluttered Scenes"
  ☆55Updated 2 years ago
• Dandelight / graspnet-baseline
  Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020)
  ☆22Updated 3 years ago
• mahaoxiang822 / dgcan
  Official implementation for ICRA2023 paper "RGB-D Grasp Detection via Depth Guided Learning with Cross-modal Attention"
  ☆16Updated 2 years ago
• sunhan1997 / easy-dexnet_vis
  Grasp pose sampling and visualization
  ☆15Updated last year
• junzastar / DFTr_Voting
  [ICCV'23] Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimation
  ☆46Updated last year
• GouMinghao / rgb_matters
  Implementation for ICRA 2021 paper "RGB Matters: Learning 7-DoF Grasp Poses on Monocular RGBD Images"
  ☆71Updated 3 years ago
• HZWang96 / PEGG-Net
  PEGG-Net: Pixel-Wise Efficient Grasp Generation in Complex Scenes (IEEE CIS-RAM 2024)
  ☆21Updated 10 months ago
• kmittle / Grasp-Detection-NBMOD
  This is the repository for the NBMOD dataset and the code of the paper "NBMOD: Find It and Grasp It in Noisy Background.
  ☆51Updated 2 years ago
• THU-VCLab / HGGD
  Official code of paper "Efficient Heatmap-Guided 6-Dof Grasp Detection in Cluttered Scenes"
  ☆109Updated last month
• yhan9848 / MP6D
  An RGB-D Dataset for Metal Parts’ 6D Pose Estimation
  ☆15Updated 2 years ago
• YangHai-1218 / SCFlow
  Shape-Constraint Recurrent Flow for 6D Object Pose Estimation (CVPR 2023)
  ☆61Updated last year
• PKU-EPIC / GraspNeRF
  [ICRA 2023] GraspNeRF: Multiview-based 6-DoF Grasp Detection for Transparent and Specular Objects Using Generalizable NeRF
  ☆182Updated last year
• PKU-EPIC / DREDS
  [ECCV 2022] Domain Randomization-Enhanced Depth Simulation and Restoration for Perceiving and Grasping Specular and Transparent Objects
  ☆143Updated last year
• rhett-chen / graspness_implementation
  My implementation of Graspnet Graspness.
  ☆218Updated 2 years ago
• lyltc1 / HiPose
  ☆36Updated 4 months ago
• zhujunli1993 / SwinDePose
  ☆53Updated last year
• TX-Leo / Graspness_6dof_robotic_grasping
  6-Dof Robotic Grasping based on "Graspness"
  ☆20Updated 2 years ago
• ck-kai / SGPA
  [ICCV'21] SGPA: Structure-Guided Prior Adaptation for Category-Level 6D Object Pose Estimation
  ☆44Updated 3 years ago
• HP-CAO / 6IMPOSE
  ☆17Updated last year
• Lynne-Zheng-Linfang / HS-Pose
  HS-Pose (CVPR 2023). Pytorch implementation of HS-Pose: Hybrid Scope Feature Extraction for Category-level Object Pose Estimation.
  ☆51Updated 2 years ago
• lolrudy / GPV_Pose
  pytorch implementation of GPV-Pose
  ☆81Updated 2 years ago
• iSEE-Laboratory / EconomicGrasp
  (ECCV 2024) Official implementation of the Economic 6-DoF Grasp Detection Framework (EconomicGrasp).
  ☆90Updated 4 months ago
• royzhang12 / Target-referenced-Reactive-Grasping-for-Dynamic-Objects
  ☆17Updated 2 years ago