# RuihengZhang/IFSOD-dataset

Dataset approched by A Benchmark and Frequency Compression Method for Infrared Few-Shot Object Detection

Repository: https://github.com/RuihengZhang/IFSOD-dataset
Canonical: https://ross.abutalabs.com/products/ifsod-dataset
License Family: other
Last push: 2025-04-03T05:40:39+00:00

## Health v2 (maintenance only)
Score: 28/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 14, release rhythm 35, longevity 46
- inputs: {"age_days": 655, "days_push": 517, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1005, forks 3 (observed 2026-09-03T02:15:08.055584+00:00)

## What it is
IFSOD is a benchmark dataset for infrared few-shot object detection, containing 4,815+ images with 23,000+ annotations across 18 categories and 12 scenarios. It ships with predefined base/novel class splits following the TFA few-shot detection protocol.

## Use cases
- train few-shot object detection models on infrared imagery
- benchmark infrared object detection algorithms
- evaluate novel-class generalization with 10-shot splits
- research military and civilian target detection in thermal images
- compare against M3FD and RGB-T234 infrared datasets

## When to choose
- you need labeled infrared images for few-shot detection research
- you want standardized base/novel splits matching the FSDet setting
- your work targets thermal/night-vision object detection benchmarks

## When to avoid
- you need large-scale RGB or RGB-T paired data
- you require a permissive open-source license for commercial use
- you need video or multimodal infrared-visible datasets

## Facets
- artifact type: dataset
- maturity: active
- function: computer-vision, machine-learning, data-science
- domain: computer-vision, machine-learning, deep-learning
- platform: cross-platform
- tags: infrared-imaging, few-shot-learning, object-detection, benchmark-dataset, thermal-imaging

## Member repositories
- RuihengZhang/IFSOD-dataset (main) score 28

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:08.055584+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:13:08.017513+00:00, confidence not recorded.
  - readme: https://github.com/RuihengZhang/IFSOD-dataset (fetched 2026-09-03T02:15:08.055584+00:00, sha 3af72ce01bbc)
- Data as of 2026-08-30T08:39:29.467469+00:00.