Implementations of few-shot object detection benchmarks
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Updated
Nov 21, 2023 - Python
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
Official code of the paper "Fine-Grained Prototypes Distillation for Few-Shot Object Detection (AAAI 2024)"
Code for ICCV 2021 paper: 'Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networks'
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
Hadwritten Text Recognition in Few-shot Scenario
Few-Shot Object Detection with Transformer
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