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Cross-Domain Few-Shot

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하위 태스크

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평가표

9

보존된 평가 기록

76

코드

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

https://github.com/Alibaba-AAIG/SSL-FEW-SHOT

공식 코드

Self-Supervised Learning For Few-Shot Image Classification

https://github.com/BaiShuanghao/CDFSC-MLP

공식 코드

Improving Cross-domain Few-shot Classification with Multilayer Perceptron

https://github.com/FatemehAskari/MSENet

공식 코드

Enhancing Few-Shot Image Classification through Learnable Multi-Scale Embedding and Attention Mechanisms

https://github.com/Haoqing-Wang/CDFSL-ATA

공식 코드

Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

https://github.com/LONGXUANX/CDFormer_code

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

https://github.com/SunJiamei/few-shot-lrp-guided

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Explanation-Guided Training for Cross-Domain Few-Shot Classification

https://github.com/TJU-YDragonW/TAMT

공식 코드

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition

https://github.com/Tsingularity/FRN

공식 코드

Few-Shot Classification with Feature Map Reconstruction Networks

https://github.com/TungChintao/APM

공식 코드

Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation

https://github.com/VICO-UoE/URL

공식 코드

Cross-domain Few-shot Learning with Task-specific Adapters

https://github.com/YangYongJin/APEX

공식 코드

Leveraging Normalization Layer in Adapters With Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning

https://github.com/YazhouZhu19/RobustEMD

공식 코드

RobustEMD: Domain Robust Matching for Cross-domain Few-shot Medical Image Segmentation

https://github.com/Zhen-ao/BSDB-CDFSL_Track

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Ensemble Model with Batch Spectral Regularization and Data Blending for Cross-Domain Few-Shot Learning with Unlabeled Data

https://github.com/alinlab/psco

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Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning

https://github.com/arjish/PreTrainedFullLibrary_FewShot

공식 코드

Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier

https://github.com/asrafulashiq/dynamic-cdfsl

공식 코드

Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data

https://github.com/bbbdylan/unisiam

공식 코드

Self-Supervision Can Be a Good Few-Shot Learner

https://github.com/bupt-ai-cz/restnet

공식 코드

RestNet: Boosting Cross-Domain Few-Shot Segmentation with Residual Transformation Network

https://github.com/chenjiayi68/dmtnet

공식 코드

Cross-Domain Few-Shot Semantic Segmentation via Doubly Matching Transformation

https://github.com/cvl-hub/gprn

공식 코드

SAM-Aware Graph Prompt Reasoning Network for Cross-Domain Few-Shot Segmentation

https://github.com/debabratapal7/dafosnet

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Domain Adaptive Few-Shot Open-Set Learning

https://github.com/frkl/modular-adaptation

공식 코드

Modular Adaptation for Cross-Domain Few-Shot Learning

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

공식 코드

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

https://github.com/google-research/meta-dataset

공식 코드

Cross-domain Few-shot Learning with Task-specific Adapters

https://github.com/henulwy/stbdip

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Multi-level Relation Learning for Cross-domain Few-shot Hyperspectral Image Classification

https://github.com/hlings/acrofod

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AcroFOD: An Adaptive Method for Cross-domain Few-shot Object Detection

https://github.com/hongyujerrywang/featureextractorstacking

공식 코드

Feature Extractor Stacking for Cross-domain Few-shot Learning

https://github.com/hytseng0509/CrossDomainFewShot

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Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation

https://github.com/icvteam/dara

공식 코드

Dual Adaptive Representation Alignment for Cross-domain Few-shot Learning

https://github.com/jarucezh/cldfd

공식 코드

Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot Classification

https://github.com/jaychempan/ETS

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Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object Detection

https://github.com/johncai117/DAMSL

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DAMSL: Domain Agnostic Meta Score-based Learning

https://github.com/johnmaijer/x-few-_cd-fsod

공식 코드

NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Results

https://github.com/kavehhassani/metagrl

공식 코드

Cross-Domain Few-Shot Graph Classification

https://github.com/lisuyi/pbadv_czsl

공식 코드

Contextual Interaction via Primitive-based Adversarial Training For Compositional Zero-shot Learning

https://github.com/lovelyqian/CDFSOD-benchmark

공식 코드

Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.