facebookresearch/neuralfeels — explained in plain English
Analysis updated 2026-07-17 · repo last pushed 2024-11-13
Train or run a neural model that fuses vision and tactile sensor data to reconstruct a held object's 3D shape.
Use the provided datasets and trained models to study vision-touch fusion for robot manipulation research.
Build dexterous manipulation tasks like assembly or sorting that need full 3D understanding of a grasped object.
| facebookresearch/neuralfeels | facebookresearch/iopath | vila-lab/figmirror | |
|---|---|---|---|
| Stars | 153 | 153 | 153 |
| Language | Python | Python | Python |
| Last pushed | 2024-11-13 | 2026-06-25 | — |
| Maintenance | Stale | Active | — |
| Setup difficulty | hard | — | moderate |
| Complexity | 5/5 | — | 3/5 |
| Audience | researcher | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
Requires a powerful GPU and a nontrivial installation process to get the neural field pipeline running.
A research system that combines camera vision and touch-sensor data into a neural model so a robot hand can track and reconstruct the 3D shape of an object it's holding, even novel or partially hidden ones.
Mainly Python. The stack also includes Python, PyTorch, CUDA.
Stale — no commits in 1-2 years (last push 2024-11-13).
Setup difficulty is rated hard, with roughly 1day+ to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
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