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Few-Shot Object Detection

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Few-Shot Object Detection is a computer vision task that involves detecting objects in images with limited training data. The goal is to train a model on a few examples of each object class and then use the model to detect objects in new images.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/16337093/PnP-FSOD

공식 코드

Instant Response Few-shot Object Detection with Meta Strategy and Explicit Localization Inference

https://github.com/Bohao-Lee/CME

공식 코드

Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detection

https://github.com/Computer-Vision-in-the-Wild/Elevater_Toolkit_IC

공식 코드

ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models

https://github.com/GuangxingHan/QA-FewDet

공식 코드

Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networks

https://github.com/INFINIQ-AI1/RISF

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Re-Scoring Using Image-Language Similarity for Few-Shot Object Detection

https://github.com/JialianW/Forest_RCNN

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Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation

https://github.com/LONGXUANX/CDFormer_code

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CDFormer: Cross-Domain Few-Shot Object Detection Transformer Against Feature Confusion

https://github.com/Megvii-BaseDetection/GFSD

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Generalized Few-Shot Object Detection without Forgetting

https://github.com/MegviiDetection/FSCE

공식 코드

FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding

https://github.com/RuoyuChen10/CCL-FSOD

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Generalized Semantic Contrastive Learning via Embedding Side Information for Few-Shot Object Detection

https://github.com/Tung-I/Dual-awareness-Attention-for-Few-shot-Object-Detection

공식 코드

Dual-Awareness Attention for Few-Shot Object Detection

https://github.com/Ze-Yang/Context-Transformer

공식 코드

Context-Transformer: Tackling Object Confusion for Few-Shot Detection

https://github.com/ZhangGongjie/Meta-DETR

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Meta-DETR: Image-Level Few-Shot Object Detection with Inter-Class Correlation Exploitation

https://github.com/amajee11us/smile-fsod

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SMILe: Leveraging Submodular Mutual Information For Robust Few-Shot Object Detection

https://github.com/amazon-research/few-shot-object-detection-benchmark

공식 코드

Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark

https://github.com/amingwu/up-fsod

공식 코드

Universal-Prototype Enhancing for Few-Shot Object Detection

https://github.com/amirbar/detreg

공식 코드

DETReg: Unsupervised Pretraining with Region Priors for Object Detection

https://github.com/anishmadan23/foundational_fsod

공식 코드

Revisiting Few-Shot Object Detection with Vision-Language Models

https://github.com/asra-aslam/unseennet

공식 코드

UnseenNet: Fast Training Detector for Any Unseen Concept

https://github.com/bethgelab/siamese-mask-rcnn

공식 코드

One-Shot Instance Segmentation

https://github.com/bingykang/Fewshot_Detection

공식 코드

Few-shot Object Detection via Feature Reweighting

https://github.com/bohao-lee/pdc

공식 코드

Proposal Distribution Calibration for Few-Shot Object Detection

https://github.com/computer-vision-in-the-wild/cvinw_readings

공식 코드

ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models

https://github.com/csuhan/vfa

공식 코드

Few-Shot Object Detection via Variational Feature Aggregation

https://github.com/danhntd/FS-CDIS

공식 코드

The Art of Camouflage: Few-Shot Learning for Animal Detection and Segmentation

https://github.com/deku-0621/tide

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TIDE: Test Time Few Shot Object Detection

https://github.com/ebennequin/FewShotVision

공식 코드

Meta-learning algorithms for Few-Shot Computer Vision

https://github.com/er-muyue/defrcn

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DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection

https://github.com/facebookresearch/Detic

공식 코드

Detecting Twenty-thousand Classes using Image-level Supervision

https://github.com/facebookresearch/detectron2/tree/main/projects/ViTDet

공식 코드

Exploring Plain Vision Transformer Backbones for Object Detection

https://github.com/facebookresearch/sylph-few-shot-detection

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Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection

https://github.com/fanq15/FewX

공식 코드

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector

https://github.com/fsod/cd-fsod

공식 코드

CD-FSOD: A Benchmark for Cross-domain Few-shot Object Detection

https://github.com/gabrielhuang/awesome-few-shot-object-detection

공식 코드

A Survey of Self-Supervised and Few-Shot Object Detection

https://github.com/gaoyingjay/ps-ttl

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PS-TTL: Prototype-based Soft-labels and Test-Time Learning for Few-shot Object Detection

https://github.com/griffbr/tfod

공식 코드

Mobile Robot Manipulation using Pure Object Detection

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