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Domain Adaptation

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하위 태스크: 13
평가표: 58
보존된 평가 기록: 391

Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.

Further readings:

A Brief Review of Domain Adaptation

<span style="color:grey; opacity: 0.6">( Image credit: Unsupervised Image-to-Image Translation Networks )</span>

코드

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

https://github.com/Erosinho13/FedDrive

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FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving

https://github.com/Evgeneus/Graph-Domain-Adaptaion

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Curriculum Graph Co-Teaching for Multi-Target Domain Adaptation

https://github.com/Externalhappy/DPA

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DPA: Dual Prototypes Alignment for Unsupervised Adaptation of Vision-Language Models

https://github.com/FengHZ/KD3A

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KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation

https://github.com/FlyHighest/UnrealPerson

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UnrealPerson: An Adaptive Pipeline towards Costless Person Re-identification

https://github.com/FlyingRoastDuck/ACT_AAAI20

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Asymmetric Co-Teaching for Unsupervised Cross Domain Person Re-Identification

https://github.com/GSidiropoulos/kgsqa_for_unseen_domains

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Knowledge Graph Simple Question Answering for Unseen Domains

https://github.com/GT-RIPL/DomainGeneralization-Stylization

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Frustratingly Simple Domain Generalization via Image Stylization

https://github.com/Gabrielcb/Unsupervised_selfAdaptative_ReID

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Unsupervised and self-adaptative techniques for cross-domain person re-identification

https://github.com/Gahyeonkim09/AAPL

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AAPL: Adding Attributes to Prompt Learning for Vision-Language Models

https://github.com/GanlongZhao/CST_DA_detection

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Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection

https://github.com/GaoLii/DSP

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DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation

https://github.com/GauriGupta19/Domain-Generalisation-in-Invariance

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Domain Generalization In Robust Invariant Representation

https://github.com/GongShuai8210/PLAN

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Federated Domain Generalization via Prompt Learning and Aggregation

https://github.com/Gorilla-Lab-SCUT/UB2DA

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On Universal Black-Box Domain Adaptation

https://github.com/GuangmingZhu/SketchIME

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Sketch Input Method Editor: A Comprehensive Dataset and Methodology for Systematic Input Recognition

https://github.com/Guru-Uni-siegen/Domain-Shifting-Network

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A Simple Domain Shifting Networkfor Generating Low Quality Images

https://github.com/HAAClassic/AdaTreeFormer

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AdaTreeFormer: Few Shot Domain Adaptation for Tree Counting from a Single High-Resolution Image

https://github.com/HAHA-DL/Episodic-DG

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Episodic Training for Domain Generalization

https://github.com/HCPLab-SYSU/CD-FER-Benchmark

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Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph Learning

https://github.com/HCPLab-SYSU/MSDA

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Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift

https://github.com/HKUST-KnowComp/FisherDA

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Fisher Deep Domain Adaptation

https://github.com/HKUST-KnowComp/NeuralSubgraphCounting

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Neural Subgraph Isomorphism Counting

https://github.com/HanjiangHu/DASGIL

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DASGIL: Domain Adaptation for Semantic and Geometric-aware Image-based Localization

https://github.com/HaohanWang/PAR

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Learning Robust Global Representations by Penalizing Local Predictive Power

https://github.com/HaohanWang/PAR_experiments

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Learning Robust Global Representations by Penalizing Local Predictive Power

https://github.com/HaokunChen245/DFDG

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Towards Data-Free Domain Generalization

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

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Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

https://github.com/Haoxiang-Wang/gradual-domain-adaptation

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Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond

https://github.com/HardworkingPearl/EDG-DDA

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Foresee What You Will Learn: Data Augmentation for Domain Generalization in Non-stationary Environment

https://github.com/HealthX-Lab/DiffusionSynCTSeg

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CT-based brain ventricle segmentation via diffusion Schrödinger Bridge without target domain ground truths

https://github.com/HeliosZhao/M3L

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Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification

https://github.com/Heliot7/open-set-da

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Open Set Domain Adaptation for Image and Action Recognition

https://github.com/HelloZicky/DUET

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DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization

https://github.com/HopkinsKwong/MFM-DA

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MFM-DA: Instance-Aware Adaptor and Hierarchical Alignment for Efficient Domain Adaptation in Medical Foundation Models

https://github.com/HosseinSimchi/META-IQA-CMRImages

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A Generalised Deep Meta-Learning Model for Automated Quality Control of Cardiovascular Magnetic Resonance Images

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