Implementations of few-shot object detection benchmarks

[T-PAMI 2022] Meta-DETR for Few-Shot Object Detection: Official PyTorch Implementation

FewX is an open-source toolbox on top of Detectron2 for data-limited instance-level recognition tasks.

(ECCV 2020) PyTorch implementation of paper "Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild"

Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection, CVPR 2021

Official code of the paper "Few-Shot Object Detection via Variational Feature Aggregation" (AAAI 2023)

Code for AAAI 2022 Oral paper: 'Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment'

Code for CVPR 2022 Oral paper: 'Few-Shot Object Detection with Fully Cross-Transformer'

Full conference version of AirDet: Few-Shot Detection without Fine-tuning for Autonomous Exploration

[ICCV 2023] Integrally Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection

Few-shot Object Counting and Detection (ECCV 2022)

(ECCV2022) The official PyTorch implementation of the "AcroFOD: An Adaptive Method for Cross-domain Few-shot Object Detection".

Awesome Few-shot learning

[AISTATS 2024] Label-Efficient Detection Toolbox and Benchmark

Code for ICCV 2021 paper: 'Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networks'

Official code of the paper "Fine-Grained Prototypes Distillation for Few-Shot Object Detection (AAAI 2024)"

This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"

Hadwritten Text Recognition in Few-shot Scenario

ROS wrapper for AirDet

Few-Shot Object Detection with Transformer