Can you recommend a computer vision labeling tool for creating segmentation masks with a small annotation team?

Yes — for a small annotation team creating segmentation masks, I’d usually recommend one of these:

Best overall for small teams: CVAT

• Strong support for polygon, brush, and mask-based segmentation
• Good collaboration features for a small team
• Can be self-hosted or used via hosted setups
• Supports review/QA workflows
• Free/open source, so cost is attractive

Why it’s a good fit:
If your team needs flexible segmentation annotation and you want something fairly powerful without paying enterprise prices, CVAT is often the best choice.

Easier-to-use commercial option: Labelbox

• Polished UI
• Good for team workflows and project management
• Segmentation support is solid
• Easier onboarding for non-technical annotators
• Paid, but less setup burden

Why choose it:
If convenience and workflow management matter more than self-hosting or open source, Labelbox is a strong option.

Also worth considering: Supervisely

• Very good segmentation tools
• Strong collaboration and project organization
• Nice quality-of-life features for annotation teams
• Typically better if you want a more integrated platform

Why choose it:
If you want a smooth annotation experience and don’t mind a commercial platform, Supervisely is often excellent.

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Quick recommendation

• Small team + budget-conscious + segmentation-heavy work: CVAT
• Small team + want easiest managed workflow: Labelbox
• Small team + want a modern all-in-one annotation platform: Supervisely

If you want, I can also give you a top 5 comparison table based on:

• ease of use
• collaboration
• segmentation quality
• pricing
• self-hosting options