Papers with Code 아카이브

Domain Adaptation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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/woldier/siamseg

공식 코드

SiamSeg: Self-Training with Contrastive Learning for Unsupervised Domain Adaptation Semantic Segmentation in Remote Sensing

https://github.com/wonderseven/lssae

공식 코드

Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencoder

https://github.com/woodwindhu/dts

공식 코드

Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection

https://github.com/woqingdoua/imbalanceclass

공식 코드

Unsupervised Reinforcement Adaptation for Class-Imbalanced Text Classification

https://github.com/workerbcd/dct

공식 코드

Domain-aware Triplet loss in Domain Generalization

https://github.com/wshi83/medadapter

공식 코드

MedAdapter: Efficient Test-Time Adaptation of Large Language Models towards Medical Reasoning

https://github.com/wufan-cse/g-nas

공식 코드

G-NAS: Generalizable Neural Architecture Search for Single Domain Generalization Object Detection

https://github.com/wuyou3474/mambanut

공식 코드

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning

https://github.com/wwwfan628/da-aim

공식 코드

Exploiting Instance-based Mixed Sampling via Auxiliary Source Domain Supervision for Domain-adaptive Action Detection

https://github.com/wyf-accept/backtoreality

공식 코드

Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label Enhancement

https://github.com/wyf0912/LDDG

공식 코드

Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization

https://github.com/wyharveychen/CloserLookFewShot

공식 코드

A Closer Look at Few-shot Classification

https://github.com/wzell/cmd

공식 코드

Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning

https://github.com/wzell/funcregr4domgen

공식 코드

Domain Generalization by Functional Regression

https://github.com/wzell/mann

공식 코드

Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment

https://github.com/x-coral/wda

공식 코드

Weakly-Supervised Cross-Domain Segmentation of Electron Microscopy with Sparse Point Annotation

https://github.com/x-ytong/DPA

공식 코드

Enabling Country-Scale Land Cover Mapping with Meter-Resolution Satellite Imagery

https://github.com/xarwinm/competence_estimation

공식 코드

Finding Competence Regions in Domain Generalization

https://github.com/xavierohan/AdaClust_DomainBed

공식 코드

Adaptive Methods for Aggregated Domain Generalization

https://github.com/xbq1994/meta

공식 코드

Mimic Embedding via Adaptive Aggregation: Learning Generalizable Person Re-identification

https://github.com/xc-zhonghit/eeg-dg

공식 코드

EEG-DG: A Multi-Source Domain Generalization Framework for Motor Imagery EEG Classification

https://github.com/xdeng7/scale-aware_da

공식 코드

Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery

https://github.com/xhu248/cisfa_da

공식 코드

Contrastive Image Synthesis and Self-supervised Feature Adaptation for Cross-Modality Biomedical Image Segmentation

https://github.com/xhz0809/openstance

공식 코드

OpenStance: Real-world Zero-shot Stance Detection

https://github.com/xhz0809/x-shot

공식 코드

X-Shot: A Unified System to Handle Frequent, Few-shot and Zero-shot Learning Simultaneously in Classification

https://github.com/xiang-pan/projectionnet

공식 코드

Bridging Domains with Approximately Shared Features

https://github.com/xiangdal/implicit_alignment

공식 코드

Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation

https://github.com/xiangyue9607/qve

공식 코드

Synthetic Question Value Estimation for Domain Adaptation of Question Answering

https://github.com/xiaoachen98/DDB

공식 코드

Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation

https://github.com/xiaoachen98/daln

공식 코드

Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation

https://github.com/xiaoaoran/SynLiDAR

공식 코드

Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation

https://github.com/xiaoaoran/polarmix

공식 코드

PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds

https://github.com/xiaobai1217/DomainAdaptation

공식 코드

Audio-Adaptive Activity Recognition Across Video Domains

https://github.com/xiaohao-xu/slam-under-perturbation

공식 코드

Scalable Benchmarking and Robust Learning for Noise-Free Ego-Motion and 3D Reconstruction from Noisy Video

https://github.com/xiaohulugo/t-ro2024-dali

공식 코드

DALI: Domain Adaptive LiDAR Object Detection via Distribution-level and Instance-level Pseudo Label Denoising

https://github.com/xiaoleihuang/domainfairness

공식 코드

Easy Adaptation to Mitigate Gender Bias in Multilingual Text Classification

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