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metadata
license: cc-by-4.0
language:
- en
pipeline_tag: robotics
tags:
- Grasping
- Manipulation
- IA
- Transformers
- CVAE
CoToGrasp: Contact-Topology-Conditioned Dexterous Grasp Synthesis via Canonical Workspace Learning
Julien Mérand1, Boris Meden1, Liming Chen2, Mathieu Grossard1
1Université Paris-Saclay, CEA-List 2École Centrale de Lyon, CNRS, LIRIS, UMR5205, Institut Universitaire de France (IUF)
19th European Conference on Computer Vision (ECCV 2026)
CoToGrasp is a novel generative framework that synthesizes diverse and stable grasps strictly conditioned on specific contact topologies.
See https://github.com/CEA-LIST/CoToGrasp for full code and instructions.
Your directory tree should strictly follow this structure:
# Model Checkpoints
COTOGRASP # Main folder
├── ...
├── logs # ckpts folder
├── allegro_right_goag_dgcnn_types_2_0209
└── shadowhand_goag_dgcnn_types_2_0128
└── ...
# Dataset Directory
COTOGRASP_DATA
├── handprints
├── pointclouds
├── dexgraspnet
├── multidex
├── contactdb
└── ycb
├── urdf
├── objects
├── dexgraspnet
├── multidex
└── robot
└── workspaces