ucbdrive/few-shot-object-detection

Health v2 · maintenance only

Adoption not part of the score

1218 stars · 223 forks observed · 2026-08-28

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

FsDet is the official implementation of the ICML 2020 paper 'Frustratingly Simple Few-Shot Object Detection' (TFA), built on detectron2. It provides few-shot object detection benchmarks on PASCAL VOC, COCO, and LVIS with pre-trained models and a modular framework for future research.

Use cases

• run few-shot object detection benchmarks on VOC, COCO, and LVIS
• reproduce TFA results from the ICML 2020 paper
• fine-tune an object detector on a few novel-class examples
• download pre-trained few-shot detection models
• build and evaluate new few-shot detection methods on a modular framework

When to choose

• you need standardized few-shot object detection benchmarks and splits
• you want to reproduce or compare against the TFA approach
• you are doing research on few-shot learning for detection and want a detectron2-based base

When to avoid

• you need general-purpose object detection rather than few-shot settings
• you need a production-ready detection system rather than research code
• you require frequent updates or support for the latest detectron2 versions

Facets

library · maturity maintenance

machine-learning computer-vision benchmarking machine-learning computer-vision artificial-intelligence python few-shot-learning object-detection detectron2 research-code tfa gpu linux

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