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Domain Adaptation

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하위 태스크: 13
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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/bloomberry/lada

공식 코드

Semi-Supervised Domain Adaptation for Wildfire Detection

https://github.com/blue-531/talos

공식 코드

TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight

https://github.com/blueGorae/DynaGAN

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DynaGAN: Dynamic Few-shot Adaptation of GANs to Multiple Domains

https://github.com/bobrown/ccda_lgfa

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Curriculum-style Local-to-global Adaptation for Cross-domain Remote Sensing Image Segmentation

https://github.com/bolajiy/golden-retriever

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Written Term Detection Improves Spoken Term Detection

https://github.com/bomb2peng/learn3D

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Learning Pose-invariant 3D Object Reconstruction from Single-view Images

https://github.com/bonifazstuhr/feamgan

공식 코드

Towards Unsupervised Representation Learning: Learning, Evaluating and Transferring Visual Representations

https://github.com/borgwardtlab/jointmds

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Unsupervised Manifold Alignment with Joint Multidimensional Scaling

https://github.com/boschresearch/aldm

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Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive

https://github.com/boschresearch/issa

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Intra-Source Style Augmentation for Improved Domain Generalization

https://github.com/boschresearch/tada

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TADA: Efficient Task-Agnostic Domain Adaptation for Transformers

https://github.com/bostoncake/c-visdit

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Confidence-based Visual Dispersal for Few-shot Unsupervised Domain Adaptation

https://github.com/boudinfl/silk

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Unsupervised Domain Adaptation for Keyphrase Generation using Citation Contexts

https://github.com/boyanglyu/dg_via_wb

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Barycentric-alignment and reconstruction loss minimization for domain generalization

https://github.com/bplank/awesome-neural-adaptation-in-NLP

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Neural Unsupervised Domain Adaptation in NLP---A Survey

https://github.com/bplank/semi-supervised-baselines

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Strong Baselines for Neural Semi-supervised Learning under Domain Shift

https://github.com/bradyz/task-distillation

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Domain Adaptation Through Task Distillation

https://github.com/brandstetter-johannes/mp-neural-pde-solvers

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Message Passing Neural PDE Solvers

https://github.com/brdav/cma

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Contrastive Model Adaptation for Cross-Condition Robustness in Semantic Segmentation

https://github.com/brdav/refign

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Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions

https://github.com/brucewlee/prompt-learning-readability

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Prompt-based Learning for Text Readability Assessment

https://github.com/btknzn/TiagoRobotSkillLearning

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Robot Skill Learning Via Classical Robotics-Based Generated Datasets: Advantages, Disadvantages, and Future Improvement

https://github.com/bubblybingbong/augmentationsegmentation

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Enhancing Autonomous Vehicle Perception in Adverse Weather through Image Augmentation during Semantic Segmentation Training

https://github.com/bupt-ai-cz/IAST-ECCV2020

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Instance Adaptive Self-Training for Unsupervised Domain Adaptation

https://github.com/bupt-ai-cz/Meta-SelfLearning

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Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark

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

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Hard-aware Instance Adaptive Self-training for Unsupervised Cross-domain Semantic Segmentation

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

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Semi-supervised Domain Adaptation via Prototype-based Multi-level Learning

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

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WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain Labels

https://github.com/busername/learning_to_diversify

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Learning to Diversify for Single Domain Generalization

https://github.com/butspeechfit/diarizen

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Efficient and Generalizable Speaker Diarization via Structured Pruning of Self-Supervised Models

https://github.com/bymavis/adv_weight_neurips2021

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Clustering Effect of (Linearized) Adversarial Robust Models

https://github.com/bzantium/bert-AAD

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Knowledge Distillation for BERT Unsupervised Domain Adaptation

https://github.com/c-juhwan/unigen

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UniGen: Universal Domain Generalization for Sentiment Classification via Zero-shot Dataset Generation

https://github.com/c0notsilly/advfrequency

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Towards Combating Frequency Simplicity-biased Learning for Domain Generalization

https://github.com/c4dm/dcase-few-shot-bioacoustic

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Mind the Domain Gap: a Systematic Analysis on Bioacoustic Sound Event Detection

https://github.com/cactilab/ugcg-guard

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Moderating Illicit Online Image Promotion for Unsafe User-Generated Content Games Using Large Vision-Language Models

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