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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/tsun/ssrt

공식 코드

Safe Self-Refinement for Transformer-based Domain Adaptation

https://github.com/tsunghan-wu/d2ada

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D2ADA: Dynamic Density-aware Active Domain Adaptation for Semantic Segmentation

https://github.com/tue-mps/vfm-uda

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Exploring the Benefits of Vision Foundation Models for Unsupervised Domain Adaptation

https://github.com/tugang-git/gla-da-for-multivariate-time-series

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GLA-DA: Global-Local Alignment Domain Adaptation for Multivariate Time Series

https://github.com/tum-aimed/octa-seg

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Synthetic optical coherence tomography angiographs for detailed retinal vessel segmentation without human annotations

https://github.com/tum-vision/scenedino

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Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion

https://github.com/twanvl/adrem

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Domain Adaptation with Randomized Expectation Maximization

https://github.com/twuilliam/open-search

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Open Cross-Domain Visual Search

https://github.com/ty-shi/freecos

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FreeCOS: Self-Supervised Learning from Fractals and Unlabeled Images for Curvilinear Object Segmentation

https://github.com/tylfromseu/dpstyler

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DPStyler: Dynamic PromptStyler for Source-Free Domain Generalization

https://github.com/uark-cviu/bimal

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BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation

https://github.com/uark-cviu/fredom

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FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding

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

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

https://github.com/ucla-mobility/v2v4real

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V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception

https://github.com/ucsc-real/model_transferability

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Model Transferability With Responsive Decision Subjects

https://github.com/udase-chime2023/jspsych-p.835-listening-test

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Objective and subjective evaluation of speech enhancement methods in the UDASE task of the 7th CHiME challenge

https://github.com/uds-lsv/da-lang-id

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Cross-Domain Adaptation of Spoken Language Identification for Related Languages: The Curious Case of Slavic Languages

https://github.com/uds-lsv/domain-adaptation-molecular-transformers

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Transformers for molecular property prediction: Domain adaptation efficiently improves performance

https://github.com/uds-lsv/llmft

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Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation

https://github.com/uds-lsv/token-is-a-mask

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TOKEN is a MASK: Few-shot Named Entity Recognition with Pre-trained Language Models

https://github.com/uhh-lt/hatespeech

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How Hateful are Movies? A Study and Prediction on Movie Subtitles

https://github.com/uiuctml/goat

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Gradual Domain Adaptation: Theory and Algorithms

https://github.com/uk-cliplab/representationjsd

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The Representation Jensen-Shannon Divergence

https://github.com/ukplab/emnlp2022-temporal-adaptation

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The challenges of temporal alignment on Twitter during crises

https://github.com/ukplab/gpl

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GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval

https://github.com/ukplab/pytorch-bertflow

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TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning

https://github.com/uliege-driving/dade

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Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic Environments

https://github.com/uliege-driving/msc-tta

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Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic Environments

https://github.com/umeannever/b2ner

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Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition

https://github.com/underwater-lab/tuda

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Domain Adaptation for Underwater Image Enhancement

https://github.com/unmannedlab/lidar-reflectivity-segmentation

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Reflectivity Is All You Need!: Advancing LiDAR Semantic Segmentation

https://github.com/uoguelph-mlrg/Cutout

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Improved Regularization of Convolutional Neural Networks with Cutout

https://github.com/upeee/GOO-GAZE2021

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GOO: A Dataset for Gaze Object Prediction in Retail Environments

https://github.com/urvashik/knnlm

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Generalization through Memorization: Nearest Neighbor Language Models

https://github.com/usaito/asymmetric-tri-rec-real

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Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback

https://github.com/usaito/ijcai2022-adversarial-mf

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Towards Resolving Propensity Contradiction in Offline Recommender Learning

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