facebookresearch / facebookresearch/sonata
Instance Segmentation
- Dominant language
- Python
- Stars
- 795
- Forks
- 56
- PR merge metrics
- No merged PRs in 30d
Description
Hi!
I've successfully implemented semantic segmentation training and testing with SONATA on ScanNet 20 but I noticed in the paper that SONATA also achieves strong instance segmentation results. I'm now trying to extend my implementation to instance segmentation but I'm unsure about the approach?
Do you have any recommendations on:
What instance segmentation head architecture works best with SONATA? Also is there any data prep that I need to do in particular?
I'd really appreciate any insights you could share. Great project btw - thank you so much for your work and being so generous with releasing the code/models!
-Alex
Contributor guide
Research direction
The issue names no files or tests. Start by locating the existing SONATA semantic-segmentation training and testing entry points and reviewing the paper's instance-segmentation setup for ScanNet 20; done means a documented, reproducible path for the requested head architecture and data preparation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100