Cutie: Putting the Object Back into Video Object Segmentation
Source: https://github.com/hkchengrex/cutie
Structured fields
{
"archived": false,
"checked_at": "2026-10-17T00:00:00.000Z",
"usefulness": "Object-level memory VOS (CVPR 2024 Highlight, UIUC + Adobe): propagates a first-frame mask through long footage; includes an interactive GUI and scripting demo. Strong open option for roto mask propagation.",
"source_type": "repository",
"availability": "available",
"source_owner": "Ho Kei Cheng et al.",
"next_check_at": "2026-10-31T00:00:00.000Z",
"upstream_updated_at": "2024-11-08T21:38:38.000Z"
}Evidence claims
- [upstream_claim] README: Cutie (UIUC and Adobe, CVPR 2024 Highlight) with arXiv link; scripting_demo.py is the suggested starting point for use in a project; GUI adds 'permanent memory' from XMem++. · locator: README, intro and usage source
- [sourced_fact] README notes the GUI uses RITM for interactive segmentation and redistributes its code in gui/ritm under RITM's license. · locator: README, acknowledgements source
- [sourced_fact] GitHub metadata: MIT, not archived, last push 2024-11-08. · locator: repository metadata source
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| code | MIT | permitted | permitted | permitted | unknown | MIT per GitHub; gui/ritm subfolder follows RITM's license. |
| model_weights | unknown | unknown | unknown | unknown | unknown | Weights license not read; training datasets may carry own terms. |