MasterBin-IIAU/UNINEXT

Health v2 · maintenance only

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Adoption not part of the score

1278 stars · 121 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

UNINEXT is the official PyTorch implementation of the CVPR 2023 paper 'Universal Instance Perception as Object Discovery and Retrieval'. It provides a unified model that handles multiple instance-level perception tasks including object detection, instance segmentation, single and multi-object tracking, video instance segmentation, and referring expression comprehension and segmentation.

Use cases

• detect and segment object instances in images
• track multiple objects in videos
• segment video objects from referring expressions
• comprehend referring expressions to localize objects
• run video instance segmentation on benchmarks like YouTube-VIS and OVIS
• benchmark a unified model across 20 instance perception tasks

When to choose

• you need one unified model covering detection, tracking, and segmentation tasks
• you want state-of-the-art baselines for referring video object segmentation or multi-object tracking
• you are reproducing or extending CVPR 2023 instance perception research

When to avoid

• you need a lightweight production-ready detector rather than a research codebase
• you lack GPU resources for training large vision models
• you need tasks outside instance-level perception such as semantic segmentation or image classification

Facets

library · maturity maintenance

computer-vision image-processing video-processing machine-learning deep-learning computer-vision image-processing deep-learning artificial-intelligence python object-detection instance-segmentation object-tracking video-object-segmentation referring-expression-comprehension unified-model cvpr-2023 research video linux gpu

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